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| <a href="marginal_8sql__in.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/* ----------------------------------------------------------------------- */</span><span class="comment">/**</span> |
| <a name="l00002"></a>00002 <span class="comment"> *</span> |
| <a name="l00003"></a>00003 <span class="comment"> * @file marginal.sql_in</span> |
| <a name="l00004"></a>00004 <span class="comment"> *</span> |
| <a name="l00005"></a>00005 <span class="comment"> * @brief SQL functions for linear regression</span> |
| <a name="l00006"></a>00006 <span class="comment"> * @date January 2011</span> |
| <a name="l00007"></a>00007 <span class="comment"> *</span> |
| <a name="l00008"></a>00008 <span class="comment"> * @sa Calculates marginal effects for various regression models.</span> |
| <a name="l00009"></a>00009 <span class="comment"> *</span> |
| <a name="l00010"></a>00010 <span class="comment"> */</span><span class="comment">/* ----------------------------------------------------------------------- */</span> |
| <a name="l00011"></a>00011 |
| <a name="l00012"></a>00012 m4_include(`SQLCommon.m4<span class="stringliteral">')</span> |
| <a name="l00013"></a>00013 <span class="stringliteral"></span> |
| <a name="l00014"></a>00014 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00015"></a>00015 <span class="comment">/**</span> |
| <a name="l00016"></a>00016 <span class="comment">@addtogroup grp_marginal</span> |
| <a name="l00017"></a>00017 <span class="comment"></span> |
| <a name="l00018"></a>00018 <span class="comment">@about</span> |
| <a name="l00019"></a>00019 <span class="comment"></span> |
| <a name="l00020"></a>00020 <span class="comment">A marginal effect (ME) or partial effect measures the effect on the</span> |
| <a name="l00021"></a>00021 <span class="comment">conditional mean of \f$ y \f$ of a change in one of the regressors, say</span> |
| <a name="l00022"></a>00022 <span class="comment">\f$X_k\f$. In the linear regression model, the ME equals the</span> |
| <a name="l00023"></a>00023 <span class="comment">relevant slope coefficient, greatly simplifying analysis. For nonlinear models,</span> |
| <a name="l00024"></a>00024 <span class="comment">we require specialized algorithms for calculating ME.</span> |
| <a name="l00025"></a>00025 <span class="comment"></span> |
| <a name="l00026"></a>00026 <span class="comment"></span> |
| <a name="l00027"></a>00027 <span class="comment">The standard approach to modeling dichotomous/binary variables</span> |
| <a name="l00028"></a>00028 <span class="comment">(so \f$y \in \{0, 1\} \f$) is to estimate a generalized linear model under the</span> |
| <a name="l00029"></a>00029 <span class="comment">assumption that \f$ y \f$ follows some form of Bernoulli distribution. Thus the expected</span> |
| <a name="l00030"></a>00030 <span class="comment">value of \f$ y \f$ becomes,</span> |
| <a name="l00031"></a>00031 <span class="comment">\f[</span> |
| <a name="l00032"></a>00032 <span class="comment"> y = G(X' \beta),</span> |
| <a name="l00033"></a>00033 <span class="comment">\f]</span> |
| <a name="l00034"></a>00034 <span class="comment"></span> |
| <a name="l00035"></a>00035 <span class="comment">where G is the specified binomial distribution. For</span> |
| <a name="l00036"></a>00036 <span class="comment">logistic regression, the funciton \f$ G \f$ represents the inverse logit function.</span> |
| <a name="l00037"></a>00037 <span class="comment"></span> |
| <a name="l00038"></a>00038 <span class="comment">In logistic regression:</span> |
| <a name="l00039"></a>00039 <span class="comment">\f[</span> |
| <a name="l00040"></a>00040 <span class="comment">P = \frac{1}{1 + e^{-(\beta_0 + \beta_1 x_1 + \dots \beta_j x_j)}}</span> |
| <a name="l00041"></a>00041 <span class="comment"> = \frac{1}{1 + e^{-z}}</span> |
| <a name="l00042"></a>00042 <span class="comment"> \implies \frac{\partial P}{\partial X_k} = \beta_k \cdot \frac{1}{1 + e^{-z}} \cdot</span> |
| <a name="l00043"></a>00043 <span class="comment"> \frac{e^{-z}}{1 + e^{-z}} \\</span> |
| <a name="l00044"></a>00044 <span class="comment"> = \beta_k \cdot P \cdot (1-P)</span> |
| <a name="l00045"></a>00045 <span class="comment">\f]</span> |
| <a name="l00046"></a>00046 <span class="comment"></span> |
| <a name="l00047"></a>00047 <span class="comment">There are several methods for calculating the marginal effects for dichotomous</span> |
| <a name="l00048"></a>00048 <span class="comment">dependent variables. This package uses the average of the marginal effects at</span> |
| <a name="l00049"></a>00049 <span class="comment">every sample observation.</span> |
| <a name="l00050"></a>00050 <span class="comment"></span> |
| <a name="l00051"></a>00051 <span class="comment">This is calculated as follows:</span> |
| <a name="l00052"></a>00052 <span class="comment">\f[</span> |
| <a name="l00053"></a>00053 <span class="comment"> \frac{\partial y}{\partial x_k} = \beta_k \frac{\sum_{i=1}^n P(y_i = 1)(1-P(y_i = 1))}{n}, \\</span> |
| <a name="l00054"></a>00054 <span class="comment"> \text{where}, P(y_i=1) = g(X^{(i)}\beta)</span> |
| <a name="l00055"></a>00055 <span class="comment">\f]</span> |
| <a name="l00056"></a>00056 <span class="comment"></span> |
| <a name="l00057"></a>00057 <span class="comment">We use the delta method for calculating standard errors on the marginal effects.</span> |
| <a name="l00058"></a>00058 <span class="comment"></span> |
| <a name="l00059"></a>00059 <span class="comment">@input</span> |
| <a name="l00060"></a>00060 <span class="comment"></span> |
| <a name="l00061"></a>00061 <span class="comment">The input parameters are expected to be of the following form:</span> |
| <a name="l00062"></a>00062 <span class="comment"><pre> <em>margins_logregr</em> (</span> |
| <a name="l00063"></a>00063 <span class="comment"> <em>sourceTable</em> VARCHAR,</span> |
| <a name="l00064"></a>00064 <span class="comment"> <em>outputTable</em> VARCHAR,</span> |
| <a name="l00065"></a>00065 <span class="comment"> <em>dependentVariable</em> VARCHAR,</span> |
| <a name="l00066"></a>00066 <span class="comment"> <em>independentVariable</em> VARCHAR,</span> |
| <a name="l00067"></a>00067 <span class="comment"> [<em>groupingCol</em> VARCHAR,</span> |
| <a name="l00068"></a>00068 <span class="comment"> <em>marginal_vars</em> INTEGER[],</span> |
| <a name="l00069"></a>00069 <span class="comment"> <em>max_iter</em> INTEGER,</span> |
| <a name="l00070"></a>00070 <span class="comment"> <em>optimizer</em> VARCHAR,</span> |
| <a name="l00071"></a>00071 <span class="comment"> <em>tolerance</em> DOUBLE PRECISION</span> |
| <a name="l00072"></a>00072 <span class="comment"> ]</span> |
| <a name="l00073"></a>00073 <span class="comment">)</pre></span> |
| <a name="l00074"></a>00074 <span class="comment"></span> |
| <a name="l00075"></a>00075 <span class="comment">For multinomial logistic regression the input parameters are expected to be of the following form:</span> |
| <a name="l00076"></a>00076 <span class="comment"><pre> <em>margins_mlogregr</em> (</span> |
| <a name="l00077"></a>00077 <span class="comment"> <em>sourceTable</em> VARCHAR,</span> |
| <a name="l00078"></a>00078 <span class="comment"> <em>outputTable</em> VARCHAR,</span> |
| <a name="l00079"></a>00079 <span class="comment"> <em>dependentVariable</em> VARCHAR,</span> |
| <a name="l00080"></a>00080 <span class="comment"> <em>independentVariable</em> VARCHAR,</span> |
| <a name="l00081"></a>00081 <span class="comment"> [<em>groupingCol</em> VARCHAR,</span> |
| <a name="l00082"></a>00082 <span class="comment"> <em>referenceCategory</em> INTEGER,</span> |
| <a name="l00083"></a>00083 <span class="comment"> <em>marginal_vars</em> INTEGER[],</span> |
| <a name="l00084"></a>00084 <span class="comment"> <em>max_iter</em> INTEGER,</span> |
| <a name="l00085"></a>00085 <span class="comment"> <em>optimizer</em> VARCHAR,</span> |
| <a name="l00086"></a>00086 <span class="comment"> <em>tolerance</em> DOUBLE PRECISION</span> |
| <a name="l00087"></a>00087 <span class="comment"> ]</span> |
| <a name="l00088"></a>00088 <span class="comment">)</pre></span> |
| <a name="l00089"></a>00089 <span class="comment"></span> |
| <a name="l00090"></a>00090 <span class="comment">\warning The \b 'groupingCol' input parameter for \e margins_logregr and \e margins_mlogregr </span> |
| <a name="l00091"></a>00091 <span class="comment">is a placeholder in the Madlib V1.0. These inputs will be implemented in a future release.</span> |
| <a name="l00092"></a>00092 <span class="comment">@usage</span> |
| <a name="l00093"></a>00093 <span class="comment"></span> |
| <a name="l00094"></a>00094 <span class="comment"><b> The Interface</b></span> |
| <a name="l00095"></a>00095 <span class="comment"></span> |
| <a name="l00096"></a>00096 <span class="comment">For logistic regression, one can call the following function</span> |
| <a name="l00097"></a>00097 <span class="comment"><pre></span> |
| <a name="l00098"></a>00098 <span class="comment">SELECT madlib.\ref margins_logregr(</span> |
| <a name="l00099"></a>00099 <span class="comment"> <em>'source_table'</em>, -- name of input table, VARCHAR</span> |
| <a name="l00100"></a>00100 <span class="comment"> <em>'out_table'</em>, -- name of output table, VARCHAR</span> |
| <a name="l00101"></a>00101 <span class="comment"> <em>'dependent_varname'</em>, -- dependent variable, VARCHAR</span> |
| <a name="l00102"></a>00102 <span class="comment"> <em>'independent_varname'</em>, -- independent variable, VARCHAR</span> |
| <a name="l00103"></a>00103 <span class="comment"> [ <em>'grouping_cols'</em>, -- comma separated list of grouping vars, VARCHAR (Default NULL)</span> |
| <a name="l00104"></a>00104 <span class="comment"> <em>'marginal_effect_variables'</em>, -- Index list (base 1) with positions representing which marginal variable to calculate, INTEGER[] (Default NULL)</span> |
| <a name="l00105"></a>00105 <span class="comment"> <em> max_iter</em>, -- Maximum number of iterations to run the logistic regression INTEGER (Default 20)</span> |
| <a name="l00106"></a>00106 <span class="comment"> <em>'optimizer'</em>, -- Optimizer used for logistic regression VARCHAR (Default & recommended 'irls')</span> |
| <a name="l00107"></a>00107 <span class="comment"> <em>tolerance</em>, -- Tolerance for the logistic regression DOUBLE PRECISION (default 1e-4)</span> |
| <a name="l00108"></a>00108 <span class="comment"> ]</span> |
| <a name="l00109"></a>00109 <span class="comment">);</span> |
| <a name="l00110"></a>00110 <span class="comment"></pre></span> |
| <a name="l00111"></a>00111 <span class="comment"></span> |
| <a name="l00112"></a>00112 <span class="comment">For multinomial logistic regression, one can call the following function</span> |
| <a name="l00113"></a>00113 <span class="comment"><pre></span> |
| <a name="l00114"></a>00114 <span class="comment">SELECT madlib.\refmargins_mlogregr(</span> |
| <a name="l00115"></a>00115 <span class="comment"> <em>'source_table'</em>, -- name of input table, VARCHAR</span> |
| <a name="l00116"></a>00116 <span class="comment"> <em>'out_table'</em>, -- name of output table, VARCHAR</span> |
| <a name="l00117"></a>00117 <span class="comment"> <em>'dependent_varname'</em>, -- dependent variable, VARCHAR</span> |
| <a name="l00118"></a>00118 <span class="comment"> <em>'independent_varname'</em>, -- independent variable, VARCHAR</span> |
| <a name="l00119"></a>00119 <span class="comment"> [ <em>'reference_category'</em>, -- Reference category for multinomial logistic regression INTEGER</span> |
| <a name="l00120"></a>00120 <span class="comment"> <em>'grouping_cols'</em>, -- comma separated list of grouping vars, VARCHAR (Default NULL)</span> |
| <a name="l00121"></a>00121 <span class="comment"> <em>'marginal_effect_variables'</em>, -- Index list (base 1) with positions representing which marginal variable to calculate, INTEGER[] (Default NULL)</span> |
| <a name="l00122"></a>00122 <span class="comment"> <em> max_iter</em>, -- Maximum number of iterations to run the logistic regression INTEGER (Default 20)</span> |
| <a name="l00123"></a>00123 <span class="comment"> <em>'optimizer'</em>, -- Optimizer used for logistic regression VARCHAR (Default & recommended 'irls')</span> |
| <a name="l00124"></a>00124 <span class="comment"> <em>tolerance</em>, -- Tolerance for the logistic regression DOUBLE PRECISION (default 1e-4)</span> |
| <a name="l00125"></a>00125 <span class="comment"> ]</span> |
| <a name="l00126"></a>00126 <span class="comment">);</span> |
| <a name="l00127"></a>00127 <span class="comment"></pre></span> |
| <a name="l00128"></a>00128 <span class="comment"></span> |
| <a name="l00129"></a>00129 <span class="comment">Output is stored in the <em>out_table</em>:</span> |
| <a name="l00130"></a>00130 <span class="comment"><pre></span> |
| <a name="l00131"></a>00131 <span class="comment">[ margins | std_err | t_stats | p_values |</span> |
| <a name="l00132"></a>00132 <span class="comment">+------+---------+-------+----------+</span> |
| <a name="l00133"></a>00133 <span class="comment"></pre></span> |
| <a name="l00134"></a>00134 <span class="comment"></span> |
| <a name="l00135"></a>00135 <span class="comment"><b> Multinomial-Logistic Regression Notes</b></span> |
| <a name="l00136"></a>00136 <span class="comment"></span> |
| <a name="l00137"></a>00137 <span class="comment">- The reference category ranges from [0, numCategories-1]. The default reference</span> |
| <a name="l00138"></a>00138 <span class="comment">category is zero.</span> |
| <a name="l00139"></a>00139 <span class="comment"></span> |
| <a name="l00140"></a>00140 <span class="comment">- The marginal effects and supporting statistics are output in the following order.</span> |
| <a name="l00141"></a>00141 <span class="comment">For a problem with K dependent variables (1, ..., K) and J categories (0,..., J-1).</span> |
| <a name="l00142"></a>00142 <span class="comment">The output is \f$ \{ m_{k_1, j_0} \ldots m_{k_K, j_{0}}, </span> |
| <a name="l00143"></a>00143 <span class="comment">m_{k_1, j_1} \ldots m_{k_K, j_{1}}, m_{k_1, j_{J-1}} \ldots m_{k_K, j_{J-1}} \} \f$.</span> |
| <a name="l00144"></a>00144 <span class="comment">The order is NOT CONSISTENT with mlogregr, robust_variance_mlogregr and clustered_variance_mlogregr.</span> |
| <a name="l00145"></a>00145 <span class="comment">This is deliberate because the interfaces of all the other functions will be moved</span> |
| <a name="l00146"></a>00146 <span class="comment">to match that used in marginal. </span> |
| <a name="l00147"></a>00147 <span class="comment"></span> |
| <a name="l00148"></a>00148 <span class="comment">- Selectively picking the marginal effects of the independent variables will return </span> |
| <a name="l00149"></a>00149 <span class="comment">the marginal effects of ALL categories associated with the independent variable.</span> |
| <a name="l00150"></a>00150 <span class="comment"></span> |
| <a name="l00151"></a>00151 <span class="comment">- Here the <em>'independent_varname'</em> can be the name of a column, which contains</span> |
| <a name="l00152"></a>00152 <span class="comment">array of numeric values. It can also have a format of string 'array[1, x1, x2, x3]',</span> |
| <a name="l00153"></a>00153 <span class="comment">where <em>x1</em>, <em>x2</em> and <em>x3</em> are all column names.</span> |
| <a name="l00154"></a>00154 <span class="comment"></span> |
| <a name="l00155"></a>00155 <span class="comment">- Here the <em>'vars'</em> is an index list (base 1) with the set of indices</span> |
| <a name="l00156"></a>00156 <span class="comment">amongst the independent variables that must be selected.</span> |
| <a name="l00157"></a>00157 <span class="comment">One can also chose <em>NULL<\em> to pick all indepependent variables.</span> |
| <a name="l00158"></a>00158 <span class="comment"></span> |
| <a name="l00159"></a>00159 <span class="comment">@examp</span> |
| <a name="l00160"></a>00160 <span class="comment">-# Create the sample data set:</span> |
| <a name="l00161"></a>00161 <span class="comment">@verbatim</span> |
| <a name="l00162"></a>00162 <span class="comment">sql> SELECT * FROM data;</span> |
| <a name="l00163"></a>00163 <span class="comment"> id | second_attack | treatment | trait_anxiety</span> |
| <a name="l00164"></a>00164 <span class="comment">----+---------------+-----------+---------------</span> |
| <a name="l00165"></a>00165 <span class="comment"> 1 | 1 | 1 | 70</span> |
| <a name="l00166"></a>00166 <span class="comment"> 3 | 1 | 1 | 50</span> |
| <a name="l00167"></a>00167 <span class="comment"> 5 | 1 | 0 | 40</span> |
| <a name="l00168"></a>00168 <span class="comment"> 7 | 1 | 0 | 75</span> |
| <a name="l00169"></a>00169 <span class="comment"> 9 | 1 | 0 | 70</span> |
| <a name="l00170"></a>00170 <span class="comment"> 11 | 0 | 1 | 65</span> |
| <a name="l00171"></a>00171 <span class="comment"> 13 | 0 | 1 | 45</span> |
| <a name="l00172"></a>00172 <span class="comment"> 15 | 0 | 1 | 40</span> |
| <a name="l00173"></a>00173 <span class="comment"> 17 | 0 | 0 | 55</span> |
| <a name="l00174"></a>00174 <span class="comment">...</span> |
| <a name="l00175"></a>00175 <span class="comment">@endverbatim</span> |
| <a name="l00176"></a>00176 <span class="comment">-# For function summary information. Run</span> |
| <a name="l00177"></a>00177 <span class="comment">@verbatim</span> |
| <a name="l00178"></a>00178 <span class="comment">sql> select margins_logregr('help');</span> |
| <a name="l00179"></a>00179 <span class="comment">OR</span> |
| <a name="l00180"></a>00180 <span class="comment">sql> select margins_logregr();</span> |
| <a name="l00181"></a>00181 <span class="comment">OR</span> |
| <a name="l00182"></a>00182 <span class="comment">sql> select margins_logregr('');</span> |
| <a name="l00183"></a>00183 <span class="comment">@endverbatim</span> |
| <a name="l00184"></a>00184 <span class="comment"></span> |
| <a name="l00185"></a>00185 <span class="comment">-# Run the logistic regression function and then compute the marginal effects of all variables in the regression:</span> |
| <a name="l00186"></a>00186 <span class="comment">@verbatim</span> |
| <a name="l00187"></a>00187 <span class="comment">sql> select margins_logregr('patients', 'result_table', 'second_attack', 'ARRAY[1, treatment, trait_anxiety]');</span> |
| <a name="l00188"></a>00188 <span class="comment">sql> select * from result_table;</span> |
| <a name="l00189"></a>00189 <span class="comment">margins | {-0.970665392796,-0.156214190168,0.0181587690137}</span> |
| <a name="l00190"></a>00190 <span class="comment">coef | {-6.36346994178179,-1.02410605239327,0.119044916668605}</span> |
| <a name="l00191"></a>00191 <span class="comment">std_err | {0.802871454422,0.292691682191,0.0137459874022}</span> |
| <a name="l00192"></a>00192 <span class="comment">t_stats | {-1.2089922832,-0.533715850748,1.32102325446}</span> |
| <a name="l00193"></a>00193 <span class="comment">p_values | {0.243212810329,0.600447858606,0.204000202116}</span> |
| <a name="l00194"></a>00194 <span class="comment"></span> |
| <a name="l00195"></a>00195 <span class="comment"></span> |
| <a name="l00196"></a>00196 <span class="comment">-# Alternate Syntax: Run the logistic regression function and then compute the marginal effects if all variables in the regression:</span> |
| <a name="l00197"></a>00197 <span class="comment">sql> select margins_logregr('patients', 'result_table', 'second_attack', 'ARRAY[1, treatment, trait_anxiety]', NULL, NULL);</span> |
| <a name="l00198"></a>00198 <span class="comment">sql> select * from result_table;</span> |
| <a name="l00199"></a>00199 <span class="comment">margins | {-0.970665392796,-0.156214190168,0.0181587690137}</span> |
| <a name="l00200"></a>00200 <span class="comment">coef | {-6.36346994178179,-1.02410605239327,0.119044916668605}</span> |
| <a name="l00201"></a>00201 <span class="comment">std_err | {0.802871454422,0.292691682191,0.0137459874022}</span> |
| <a name="l00202"></a>00202 <span class="comment">t_stats | {-1.2089922832,-0.533715850748,1.32102325446}</span> |
| <a name="l00203"></a>00203 <span class="comment">p_values | {0.243212810329,0.600447858606,0.204000202116}</span> |
| <a name="l00204"></a>00204 <span class="comment"></span> |
| <a name="l00205"></a>00205 <span class="comment"></span> |
| <a name="l00206"></a>00206 <span class="comment">-# Run the logistic regression function and then compute the marginal effects of the first variable in the regression</span> |
| <a name="l00207"></a>00207 <span class="comment">sql> select margins_logregr('patients', 'result_table', 'second_attack', 'ARRAY[1, treatment, trait_anxiety]', NULL, ARRAY[1]);</span> |
| <a name="l00208"></a>00208 <span class="comment">sql> select * from result_table;</span> |
| <a name="l00209"></a>00209 <span class="comment">margins | {-0.970665392796}</span> |
| <a name="l00210"></a>00210 <span class="comment">coef | {-6.36346994178179}</span> |
| <a name="l00211"></a>00211 <span class="comment">std_err | {0.802871454422}</span> |
| <a name="l00212"></a>00212 <span class="comment">t_stats | {-1.2089922832}</span> |
| <a name="l00213"></a>00213 <span class="comment">p_values | {0.243212810329}</span> |
| <a name="l00214"></a>00214 <span class="comment">@endverbatim</span> |
| <a name="l00215"></a>00215 <span class="comment"></span> |
| <a name="l00216"></a>00216 <span class="comment">@examp</span> |
| <a name="l00217"></a>00217 <span class="comment">-# Create the sample data set (the full dataset has 3 categories):</span> |
| <a name="l00218"></a>00218 <span class="comment">@verbatim</span> |
| <a name="l00219"></a>00219 <span class="comment">sql> SELECT * FROM data;</span> |
| <a name="l00220"></a>00220 <span class="comment"> id | feature_1 | feature_2 | category </span> |
| <a name="l00221"></a>00221 <span class="comment">----+---------------+-----------+---------------</span> |
| <a name="l00222"></a>00222 <span class="comment"> 1 | 1 | 35 | 1</span> |
| <a name="l00223"></a>00223 <span class="comment"> 3 | 2 | 33 | 0</span> |
| <a name="l00224"></a>00224 <span class="comment"> 5 | 3 | 39 | 1</span> |
| <a name="l00225"></a>00225 <span class="comment"> 7 | 1 | 37 | 1</span> |
| <a name="l00226"></a>00226 <span class="comment"> 9 | 2 | 31 | 1</span> |
| <a name="l00227"></a>00227 <span class="comment"> 11 | 3 | 36 | 1</span> |
| <a name="l00228"></a>00228 <span class="comment"> 13 | 2 | 36 | 1</span> |
| <a name="l00229"></a>00229 <span class="comment"> 15 | 2 | 36 | 0</span> |
| <a name="l00230"></a>00230 <span class="comment"> 17 | 2 | 31 | 5</span> |
| <a name="l00231"></a>00231 <span class="comment">...</span> |
| <a name="l00232"></a>00232 <span class="comment">@endverbatim</span> |
| <a name="l00233"></a>00233 <span class="comment">-# For function summary information. Run</span> |
| <a name="l00234"></a>00234 <span class="comment">@verbatim</span> |
| <a name="l00235"></a>00235 <span class="comment">sql> select margins_mlogregr('help');</span> |
| <a name="l00236"></a>00236 <span class="comment">OR</span> |
| <a name="l00237"></a>00237 <span class="comment">sql> select margins_mlogregr();</span> |
| <a name="l00238"></a>00238 <span class="comment">OR</span> |
| <a name="l00239"></a>00239 <span class="comment">sql> select margins_mlogregr('');</span> |
| <a name="l00240"></a>00240 <span class="comment">@endverbatim</span> |
| <a name="l00241"></a>00241 <span class="comment"></span> |
| <a name="l00242"></a>00242 <span class="comment">-# Run the regression function and then compute the marginal effects of all variables in the regression (see docs for detailed order)</span> |
| <a name="l00243"></a>00243 <span class="comment">@verbatim</span> |
| <a name="l00244"></a>00244 <span class="comment">sql> select margins_mlogregr('test_data', 'result_table', 'category', 'ARRAY[1, feature_1, feature_2]');</span> |
| <a name="l00245"></a>00245 <span class="comment">sql> select * from result_table;</span> |
| <a name="l00246"></a>00246 <span class="comment">margins | {0.741613239156,-0.032868883552,-0.0144502990691,-0.972055011831,0.112337273885,0.0172621628253}</span> |
| <a name="l00247"></a>00247 <span class="comment">std_err | {0.183172236055,0.044184899499,0.00332608999704,0.263532615748,0.0555196094594,0.00457999429836}</span> |
| <a name="l00248"></a>00248 <span class="comment">t_stats | {4.04872078394,-0.743894043547,-4.34453038911,-3.68855676202,2.02338011702,3.76903587663}</span> |
| <a name="l00249"></a>00249 <span class="comment">p_values | {7.43784735554e-05,0.457840607871,2.24855476205e-05,0.000292799037776,0.0444060346517,0.000217384008015}</span> |
| <a name="l00250"></a>00250 <span class="comment">@endverbatim</span> |
| <a name="l00251"></a>00251 <span class="comment"></span> |
| <a name="l00252"></a>00252 <span class="comment">-# Run the regression and compute the marginals effects for the first dependent variable (all categories) </span> |
| <a name="l00253"></a>00253 <span class="comment">@verbatim</span> |
| <a name="l00254"></a>00254 <span class="comment">sql> select margins_mlogregr('test_data', 'result_table', 'category', 'ARRAY[1, feature_1, feature_2]', 0, NULL, ARRAY[1]);</span> |
| <a name="l00255"></a>00255 <span class="comment">sql> select * from result_table;</span> |
| <a name="l00256"></a>00256 <span class="comment">margins | {0.741613239156,-0.972055011831}</span> |
| <a name="l00257"></a>00257 <span class="comment">std_err | {0.183172236055,0.263532615748}</span> |
| <a name="l00258"></a>00258 <span class="comment">t_stats | {4.04872078394,-3.68855676202}</span> |
| <a name="l00259"></a>00259 <span class="comment">p_values | {7.43784735554e-05,0.000292799037776}</span> |
| <a name="l00260"></a>00260 <span class="comment">@endverbatim</span> |
| <a name="l00261"></a>00261 <span class="comment"></span> |
| <a name="l00262"></a>00262 <span class="comment">@verbatim</span> |
| <a name="l00263"></a>00263 <span class="comment">-# For function usage information.</span> |
| <a name="l00264"></a>00264 <span class="comment">sql> select margins_mlogregr('usage');</span> |
| <a name="l00265"></a>00265 <span class="comment">@endverbatim</span> |
| <a name="l00266"></a>00266 <span class="comment"></span> |
| <a name="l00267"></a>00267 <span class="comment">@literature</span> |
| <a name="l00268"></a>00268 <span class="comment"></span> |
| <a name="l00269"></a>00269 <span class="comment"></span> |
| <a name="l00270"></a>00270 <span class="comment">[1] mfx function in STATA: http://www.stata.com/help.cgi?mfx_option</span> |
| <a name="l00271"></a>00271 <span class="comment"></span> |
| <a name="l00272"></a>00272 <span class="comment">@sa File marginal.sql_in documenting the SQL functions.</span> |
| <a name="l00273"></a>00273 <span class="comment"></span> |
| <a name="l00274"></a>00274 <span class="comment">@internal</span> |
| <a name="l00275"></a>00275 <span class="comment">@sa Namespace \ref madlib::modules::regress</span> |
| <a name="l00276"></a>00276 <span class="comment"> documenting the implementation in C++</span> |
| <a name="l00277"></a>00277 <span class="comment">@endinternal</span> |
| <a name="l00278"></a>00278 <span class="comment">*/</span> |
| <a name="l00279"></a>00279 |
| <a name="l00280"></a>00280 |
| <a name="l00281"></a>00281 |
| <a name="l00282"></a>00282 |
| <a name="l00283"></a>00283 ------------------ Marginal Logistic Regression ------------------------------ |
| <a name="l00284"></a>00284 |
| <a name="l00285"></a>00285 CREATE TYPE MADLIB_SCHEMA.marginal_logregr_result AS ( |
| <a name="l00286"></a>00286 margins DOUBLE PRECISION[], |
| <a name="l00287"></a>00287 coef DOUBLE PRECISION[], |
| <a name="l00288"></a>00288 std_err DOUBLE PRECISION[], |
| <a name="l00289"></a>00289 t_stats DOUBLE PRECISION[], |
| <a name="l00290"></a>00290 p_values DOUBLE PRECISION[] |
| <a name="l00291"></a>00291 ); |
| <a name="l00292"></a>00292 |
| <a name="l00293"></a>00293 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.marginal_logregr_step_transition( |
| <a name="l00294"></a>00294 state DOUBLE PRECISION[], |
| <a name="l00295"></a>00295 y BOOLEAN, |
| <a name="l00296"></a>00296 x DOUBLE PRECISION[], |
| <a name="l00297"></a>00297 coef DOUBLE PRECISION[]) |
| <a name="l00298"></a>00298 RETURNS DOUBLE PRECISION[] |
| <a name="l00299"></a>00299 AS 'MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00300"></a>00300 <span class="stringliteral">LANGUAGE C IMMUTABLE;</span> |
| <a name="l00301"></a>00301 <span class="stringliteral"></span> |
| <a name="l00302"></a>00302 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.marginal_logregr_step_merge_states(</span> |
| <a name="l00303"></a>00303 <span class="stringliteral"> state1 DOUBLE PRECISION[],</span> |
| <a name="l00304"></a>00304 <span class="stringliteral"> state2 DOUBLE PRECISION[])</span> |
| <a name="l00305"></a>00305 <span class="stringliteral">RETURNS DOUBLE PRECISION[]</span> |
| <a name="l00306"></a>00306 <span class="stringliteral">AS '</span>MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00307"></a>00307 <span class="stringliteral">LANGUAGE C IMMUTABLE STRICT;</span> |
| <a name="l00308"></a>00308 <span class="stringliteral"></span> |
| <a name="l00309"></a>00309 <span class="stringliteral"></span> |
| <a name="l00310"></a>00310 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.marginal_logregr_step_final(</span> |
| <a name="l00311"></a>00311 <span class="stringliteral"> state DOUBLE PRECISION[])</span> |
| <a name="l00312"></a>00312 <span class="stringliteral">RETURNS MADLIB_SCHEMA.marginal_logregr_result</span> |
| <a name="l00313"></a>00313 <span class="stringliteral">AS '</span>MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00314"></a>00314 <span class="stringliteral">LANGUAGE C IMMUTABLE STRICT;</span> |
| <a name="l00315"></a>00315 <span class="stringliteral"></span> |
| <a name="l00316"></a>00316 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00317"></a>00317 <span class="comment">/**</span> |
| <a name="l00318"></a>00318 <span class="comment"> * @brief Compute marginal effects for logistic regression.</span> |
| <a name="l00319"></a>00319 <span class="comment"> *</span> |
| <a name="l00320"></a>00320 <span class="comment"> * @param dependentVariable Column containing the dependent variable</span> |
| <a name="l00321"></a>00321 <span class="comment"> * @param independentVariables Column containing the array of independent variables</span> |
| <a name="l00322"></a>00322 <span class="comment"> * @param coef Column containing the array of the coefficients (as obtained by logregr)</span> |
| <a name="l00323"></a>00323 <span class="comment"> *</span> |
| <a name="l00324"></a>00324 <span class="comment"> * @par</span> |
| <a name="l00325"></a>00325 <span class="comment"> * To include an intercept in the model, set one coordinate in the</span> |
| <a name="l00326"></a>00326 <span class="comment"> * <tt>independentVariables</tt> array to 1.</span> |
| <a name="l00327"></a>00327 <span class="comment"> *</span> |
| <a name="l00328"></a>00328 <span class="comment"> * @return A composite value:</span> |
| <a name="l00329"></a>00329 <span class="comment"> * - <tt>margins FLOAT8[] </tt> - Array of marginal effects</span> |
| <a name="l00330"></a>00330 <span class="comment"> * - <tt>coefFLOAT8[] </tt> - The coefficients for the regression</span> |
| <a name="l00331"></a>00331 <span class="comment"> * - <tt>std_err FLOAT8[]</tt> - Array of standard-errors (calculated by the delta method),</span> |
| <a name="l00332"></a>00332 <span class="comment"> * - <tt>t_stats FLOAT8[]</tt> - Array of t-statistics</span> |
| <a name="l00333"></a>00333 <span class="comment"> * - <tt>p_values FLOAT8[]</tt> - Array of p-values</span> |
| <a name="l00334"></a>00334 <span class="comment"> *</span> |
| <a name="l00335"></a>00335 <span class="comment"> * @usage</span> |
| <a name="l00336"></a>00336 <span class="comment"> * - Get all the diagnostic statistics:\n</span> |
| <a name="l00337"></a>00337 <span class="comment"> *</span> |
| <a name="l00338"></a>00338 <span class="comment"> * <pre> SELECT marginal_logregr(<em>dependentVariable</em>,</span> |
| <a name="l00339"></a>00339 <span class="comment"> * <em>independentVariables</em>, coef)</span> |
| <a name="l00340"></a>00340 <span class="comment"> * FROM <em>dataTable</em>;</span> |
| <a name="l00341"></a>00341 <span class="comment"> * </pre></span> |
| <a name="l00342"></a>00342 <span class="comment"> */</span> |
| <a name="l00343"></a>00343 |
| <a name="l00344"></a>00344 CREATE AGGREGATE MADLIB_SCHEMA.marginal_logregr( |
| <a name="l00345"></a>00345 /*+ "dependentVariable" */ BOOLEAN, |
| <a name="l00346"></a>00346 /*+ "independentVariables" */ DOUBLE PRECISION[], |
| <a name="l00347"></a>00347 /*+ "coef" */ DOUBLE PRECISION[] )( |
| <a name="l00348"></a>00348 STYPE=DOUBLE PRECISION[], |
| <a name="l00349"></a>00349 SFUNC=MADLIB_SCHEMA.marginal_logregr_step_transition, |
| <a name="l00350"></a>00350 m4_ifdef(`__GREENPLUM__',`PREFUNC=MADLIB_SCHEMA.marginal_logregr_step_merge_states,<span class="stringliteral">')</span> |
| <a name="l00351"></a>00351 <span class="stringliteral"> FINALFUNC=MADLIB_SCHEMA.marginal_logregr_step_final,</span> |
| <a name="l00352"></a>00352 <span class="stringliteral"> INITCOND='</span>{0,0,0,0,0,0}<span class="stringliteral">'</span> |
| <a name="l00353"></a>00353 <span class="stringliteral">);</span> |
| <a name="l00354"></a>00354 <span class="stringliteral"></span> |
| <a name="l00355"></a>00355 <span class="stringliteral"></span> |
| <a name="l00356"></a>00356 <span class="stringliteral">--------------------------- Interface ----------------------------------</span> |
| <a name="l00357"></a>00357 <span class="stringliteral"></span> |
| <a name="l00358"></a>00358 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr(</span> |
| <a name="l00359"></a>00359 <span class="stringliteral"> usage_string VARCHAR -- usage string</span> |
| <a name="l00360"></a>00360 <span class="stringliteral">)</span> |
| <a name="l00361"></a>00361 <span class="stringliteral">RETURNS VARCHAR AS $$</span> |
| <a name="l00362"></a>00362 <span class="stringliteral">DECLARE</span> |
| <a name="l00363"></a>00363 <span class="stringliteral">insert_string VARCHAR;</span> |
| <a name="l00364"></a>00364 <span class="stringliteral">BEGIN</span> |
| <a name="l00365"></a>00365 <span class="stringliteral"> IF (usage_string = '</span><span class="stringliteral">' OR usage_string = '</span>help<span class="stringliteral">' OR usage_string = '</span>?<span class="stringliteral">') THEN</span> |
| <a name="l00366"></a><a class="code" href="marginal_8sql__in.html#a3286b644d2d51a8f2874896dc1b5d925">00366</a> <span class="stringliteral"> insert_string := '</span><span class="stringliteral">' ||</span> |
| <a name="l00367"></a>00367 <span class="stringliteral"> E'</span>Summary \n<span class="stringliteral">' ||</span> |
| <a name="l00368"></a>00368 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00369"></a>00369 <span class="stringliteral"> E'</span> Functionality: Calculate marginal effects <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression\n<span class="stringliteral">' ||</span> |
| <a name="l00370"></a>00370 <span class="stringliteral"> E'</span> The funciton first runs the regression and then calculates the \n<span class="stringliteral">' ||</span> |
| <a name="l00371"></a>00371 <span class="stringliteral"> E'</span> coefficients and uses them to calculate the marginal effects \n<span class="stringliteral">' ||</span> |
| <a name="l00372"></a>00372 <span class="stringliteral"> E'</span> SELECT {schema_madlib}.margins_logregr(<span class="stringliteral">''</span>source_table<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00373"></a>00373 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>output_table<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00374"></a>00374 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>dependent_variable<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00375"></a>00375 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>independent_variable<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00376"></a>00376 <span class="stringliteral"> E'</span> [,<span class="stringliteral">''</span>grouping_cols<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00377"></a>00377 <span class="stringliteral"> E'</span> , marginal_variables \n<span class="stringliteral">' ||</span> |
| <a name="l00378"></a>00378 <span class="stringliteral"> E'</span> , max_iter \n<span class="stringliteral">' ||</span> |
| <a name="l00379"></a>00379 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>optimizer<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00380"></a>00380 <span class="stringliteral"> E'</span> , tolerance \n<span class="stringliteral">' ||</span> |
| <a name="l00381"></a>00381 <span class="stringliteral"> E'</span> , verbose_mode \n<span class="stringliteral">' ||</span> |
| <a name="l00382"></a>00382 <span class="stringliteral"> E'</span> ]<span class="stringliteral">' ||</span> |
| <a name="l00383"></a>00383 <span class="stringliteral"> E'</span> );\n<span class="stringliteral">' ||</span> |
| <a name="l00384"></a>00384 <span class="stringliteral"> E'</span>For more details on <span class="keyword">function</span> usage: \n<span class="stringliteral">' ||</span> |
| <a name="l00385"></a>00385 <span class="stringliteral"> E'</span>SELECT {schema_madlib}.margins_logregr(<span class="stringliteral">''</span>usage<span class="stringliteral">''</span>) \n<span class="stringliteral">' ||</span> |
| <a name="l00386"></a>00386 <span class="stringliteral"> E'</span><span class="stringliteral">';</span> |
| <a name="l00387"></a>00387 <span class="stringliteral"> ElSIF (usage_string = '</span>usage<span class="stringliteral">') THEN</span> |
| <a name="l00388"></a>00388 <span class="stringliteral"> insert_string := '</span><span class="stringliteral">' ||</span> |
| <a name="l00389"></a>00389 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00390"></a>00390 <span class="stringliteral"> E'</span>Usage\n<span class="stringliteral">' ||</span> |
| <a name="l00391"></a>00391 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00392"></a>00392 <span class="stringliteral"> E'</span> SELECT {schema_madlib}.margins_logregr( \n<span class="stringliteral">' ||</span> |
| <a name="l00393"></a>00393 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>source_table<span class="stringliteral">''</span>, -- Name of data table \n<span class="stringliteral">' ||</span> |
| <a name="l00394"></a>00394 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>output_table<span class="stringliteral">''</span>, -- Name of result table (overwrites <span class="keywordflow">if</span> exists) \n<span class="stringliteral">' ||</span> |
| <a name="l00395"></a>00395 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>dependent_variable<span class="stringliteral">''</span>, -- Name of column <span class="keywordflow">for</span> dependent variables\n<span class="stringliteral">' ||</span> |
| <a name="l00396"></a>00396 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>independent_variable<span class="stringliteral">''</span>, -- Name of column <span class="keywordflow">for</span> independent variables\n<span class="stringliteral">' ||</span> |
| <a name="l00397"></a>00397 <span class="stringliteral"> E'</span> (can be any SQL expression that evaluates to an array)\n<span class="stringliteral">' ||</span> |
| <a name="l00398"></a>00398 <span class="stringliteral"> E'</span>[ <span class="stringliteral">''</span>group_cols<span class="stringliteral">''</span>, -- Comma separated <span class="keywordtype">string</span> with columns to group by\n<span class="stringliteral">' ||</span> |
| <a name="l00399"></a>00399 <span class="stringliteral"> E'</span> (Optional : Default NULL => no grouping) \n<span class="stringliteral">' ||</span> |
| <a name="l00400"></a>00400 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>margins_vars<span class="stringliteral">''</span>, -- Index list (base 1) representing the independent variables to compute marginal effects on \n<span class="stringliteral">' ||</span> |
| <a name="l00401"></a>00401 <span class="stringliteral"> E'</span> (Optional : Default NULL which computes marginal effects on all variables) \n<span class="stringliteral">' ||</span> |
| <a name="l00402"></a>00402 <span class="stringliteral"> E'</span> max_iter, -- Maximum number of iterations <span class="keywordflow">for</span> the <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression\n<span class="stringliteral">' ||</span> |
| <a name="l00403"></a>00403 <span class="stringliteral"> E'</span> (Optional : Default 20) \n<span class="stringliteral">' ||</span> |
| <a name="l00404"></a>00404 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>optimizer<span class="stringliteral">''</span>, -- Optimizer <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression (newton/irls, cg or igd)\n<span class="stringliteral">' ||</span> |
| <a name="l00405"></a>00405 <span class="stringliteral"> E'</span> (Optional : Default irls) \n<span class="stringliteral">' ||</span> |
| <a name="l00406"></a>00406 <span class="stringliteral"> E'</span> tolerance, -- Termination criterion <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression (relative)\n<span class="stringliteral">' ||</span> |
| <a name="l00407"></a>00407 <span class="stringliteral"> E'</span> (Optional : Default 1e-4) \n<span class="stringliteral">' ||</span> |
| <a name="l00408"></a>00408 <span class="stringliteral"> E'</span> verbose_mode, -- Verbose mode \n<span class="stringliteral">' ||</span> |
| <a name="l00409"></a>00409 <span class="stringliteral"> E'</span> (Optional : Default False) \n<span class="stringliteral">' ||</span> |
| <a name="l00410"></a>00410 <span class="stringliteral"> E'</span>]<span class="stringliteral">' ||</span> |
| <a name="l00411"></a>00411 <span class="stringliteral"> E'</span> );\n<span class="stringliteral">' ||</span> |
| <a name="l00412"></a>00412 <span class="stringliteral"> E'</span>\n<span class="stringliteral">' ||</span> |
| <a name="l00413"></a>00413 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00414"></a>00414 <span class="stringliteral"> E'</span>Output:\n<span class="stringliteral">' ||</span> |
| <a name="l00415"></a>00415 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00416"></a>00416 <span class="stringliteral"> E'</span> The output table (<span class="stringliteral">''</span>output_table<span class="stringliteral">''</span> above) has the following columns\n<span class="stringliteral">' ||</span> |
| <a name="l00417"></a>00417 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>margins<span class="stringliteral">''</span> DOUBLE PRECISION[], -- Marginal effects \n<span class="stringliteral">' ||</span> |
| <a name="l00418"></a>00418 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>std_err<span class="stringliteral">''</span> DOUBLE PRECISION[], -- Standard errors <span class="keyword">using</span> the delta method\n<span class="stringliteral">' ||</span> |
| <a name="l00419"></a>00419 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>t_stats<span class="stringliteral">''</span> DOUBLE PRECISION[], -- T-stats of the marginal effects\n<span class="stringliteral">' ||</span> |
| <a name="l00420"></a>00420 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>p_values<span class="stringliteral">''</span> DOUBLE PRECISION[], -- p-values of the marginal effects\n<span class="stringliteral">' ||</span> |
| <a name="l00421"></a>00421 <span class="stringliteral"> E'</span>\n<span class="stringliteral">' ||</span> |
| <a name="l00422"></a>00422 <span class="stringliteral"> E'</span><span class="stringliteral">';</span> |
| <a name="l00423"></a>00423 <span class="stringliteral"> ELSE</span> |
| <a name="l00424"></a>00424 <span class="stringliteral"> insert_string := '</span>No such option. Run SELECT {schema_madlib}.margins_logregr()<span class="stringliteral">';</span> |
| <a name="l00425"></a>00425 <span class="stringliteral"> END IF;</span> |
| <a name="l00426"></a>00426 <span class="stringliteral"> RETURN insert_string;</span> |
| <a name="l00427"></a>00427 <span class="stringliteral">END;</span> |
| <a name="l00428"></a>00428 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00429"></a>00429 <span class="stringliteral"></span> |
| <a name="l00430"></a>00430 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr()</span> |
| <a name="l00431"></a>00431 <span class="stringliteral">RETURNS VARCHAR AS $$</span> |
| <a name="l00432"></a>00432 <span class="stringliteral">BEGIN</span> |
| <a name="l00433"></a>00433 <span class="stringliteral"> RETURN MADLIB_SCHEMA.margins_logregr('</span><span class="stringliteral">');</span> |
| <a name="l00434"></a>00434 <span class="stringliteral">END;</span> |
| <a name="l00435"></a>00435 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00436"></a>00436 <span class="stringliteral"></span> |
| <a name="l00437"></a>00437 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00438"></a>00438 <span class="comment">/**</span> |
| <a name="l00439"></a>00439 <span class="comment"> @brief A wrapper function for the various marginal regression analyzes.</span> |
| <a name="l00440"></a>00440 <span class="comment"> *</span> |
| <a name="l00441"></a>00441 <span class="comment"> * @param source_table String identifying the input table</span> |
| <a name="l00442"></a>00442 <span class="comment"> * @param out_table String identifying the output table to be created</span> |
| <a name="l00443"></a>00443 <span class="comment"> * @param dependent_varname Column containing the dependent variable</span> |
| <a name="l00444"></a>00444 <span class="comment"> * @param input_independent_varname Column containing the array of independent variables</span> |
| <a name="l00445"></a>00445 <span class="comment"> * @param grouping_cols Set of columns to group by.</span> |
| <a name="l00446"></a>00446 <span class="comment"> * @param marginal_vars Subset of independent variables to calculate marginal effects for.</span> |
| <a name="l00447"></a>00447 <span class="comment"> * @param max_iter Maximum number of iterations</span> |
| <a name="l00448"></a>00448 <span class="comment"> * @param optimzer Optimizer to be used (newton/irls, cg or idg)</span> |
| <a name="l00449"></a>00449 <span class="comment"> * @param tolerance Resiual tolerance</span> |
| <a name="l00450"></a>00450 <span class="comment"> * @param verbose_mode Verbose mode (on/off)</span> |
| <a name="l00451"></a>00451 <span class="comment"> *</span> |
| <a name="l00452"></a>00452 <span class="comment"> * @par</span> |
| <a name="l00453"></a>00453 <span class="comment"> * To include an intercept in the model, set one coordinate in the</span> |
| <a name="l00454"></a>00454 <span class="comment"> * <tt>independentVariables</tt> array to 1.</span> |
| <a name="l00455"></a>00455 <span class="comment"> *</span> |
| <a name="l00456"></a>00456 <span class="comment"> * @return void</span> |
| <a name="l00457"></a>00457 <span class="comment"> *</span> |
| <a name="l00458"></a>00458 <span class="comment"> * @usage</span> |
| <a name="l00459"></a>00459 <span class="comment"> * For function summary information. Run</span> |
| <a name="l00460"></a>00460 <span class="comment"> * sql> select margins_logregr('help');</span> |
| <a name="l00461"></a>00461 <span class="comment"> * OR</span> |
| <a name="l00462"></a>00462 <span class="comment"> * sql> select margins_logregr();</span> |
| <a name="l00463"></a>00463 <span class="comment"> * OR</span> |
| <a name="l00464"></a>00464 <span class="comment"> * sql> select margins_logregr('?');</span> |
| <a name="l00465"></a>00465 <span class="comment"> * For function usage information. Run</span> |
| <a name="l00466"></a>00466 <span class="comment"> * sql> select margins_logregr('usage');</span> |
| <a name="l00467"></a>00467 <span class="comment"> * - Compute the coefficients, and the get the marginal diagnostic statistics:</span> |
| <a name="l00468"></a>00468 <span class="comment"> * <pre></span> |
| <a name="l00469"></a>00469 <span class="comment"> * select margins_logregr(source_table, out_table, dependentVariable, independentVariables);</span> |
| <a name="l00470"></a>00470 <span class="comment"> * </pre></span> |
| <a name="l00471"></a>00471 <span class="comment"> *</span> |
| <a name="l00472"></a>00472 <span class="comment"> */</span> |
| <a name="l00473"></a>00473 |
| <a name="l00474"></a>00474 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00475"></a>00475 source_table VARCHAR -- name of input table |
| <a name="l00476"></a>00476 , out_table VARCHAR -- name of output table |
| <a name="l00477"></a>00477 , dependent_varname VARCHAR -- name of dependent variable |
| <a name="l00478"></a>00478 , input_independent_varname VARCHAR -- name of independent variable |
| <a name="l00479"></a>00479 , input_group_cols VARCHAR -- names of columns to group by |
| <a name="l00480"></a>00480 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00481"></a>00481 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l00482"></a>00482 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l00483"></a>00483 , tolerance DOUBLE PRECISION -- Tolerance |
| <a name="l00484"></a>00484 , verbose_mode BOOLEAN -- Verbose mode |
| <a name="l00485"></a>00485 ) |
| <a name="l00486"></a>00486 RETURNS VOID AS $$ |
| <a name="l00487"></a>00487 PythonFunction(regress, marginal, margins_logregr) |
| <a name="l00488"></a>00488 $$ LANGUAGE plpythonu; |
| <a name="l00489"></a>00489 |
| <a name="l00490"></a>00490 |
| <a name="l00491"></a>00491 |
| <a name="l00492"></a>00492 -- Default Variable calls for margins_logregr |
| <a name="l00493"></a>00493 ------------------------------------------------------------------------------ |
| <a name="l00494"></a>00494 <span class="comment"></span> |
| <a name="l00495"></a>00495 <span class="comment">/**</span> |
| <a name="l00496"></a><a class="code" href="marginal_8sql__in.html#a6fc43eedb6f33e498efc03060fac7c35">00496</a> <span class="comment"> * @brief Marginal effects with default variables</span> |
| <a name="l00497"></a>00497 <span class="comment"> **/</span> |
| <a name="l00498"></a>00498 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00499"></a>00499 source_table VARCHAR -- name of input table |
| <a name="l00500"></a>00500 , out_table VARCHAR -- name of output table |
| <a name="l00501"></a>00501 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00502"></a>00502 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00503"></a>00503 ) |
| <a name="l00504"></a>00504 RETURNS VOID AS $$ |
| <a name="l00505"></a>00505 BEGIN |
| <a name="l00506"></a>00506 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00507"></a>00507 source_table, |
| <a name="l00508"></a>00508 out_table, |
| <a name="l00509"></a>00509 dependent_variable, |
| <a name="l00510"></a>00510 independent_variable, |
| <a name="l00511"></a>00511 NULL, |
| <a name="l00512"></a>00512 NULL, |
| <a name="l00513"></a>00513 20, |
| <a name="l00514"></a>00514 'irls<span class="stringliteral">',</span> |
| <a name="l00515"></a>00515 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00516"></a>00516 <span class="stringliteral"> False);</span> |
| <a name="l00517"></a>00517 <span class="stringliteral">END;</span> |
| <a name="l00518"></a>00518 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00519"></a>00519 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00520"></a>00520 <span class="comment">/**</span> |
| <a name="l00521"></a>00521 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00522"></a>00522 <span class="comment"> **/</span> |
| <a name="l00523"></a>00523 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00524"></a>00524 source_table VARCHAR -- name of input table |
| <a name="l00525"></a>00525 , out_table VARCHAR -- name of output table |
| <a name="l00526"></a>00526 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00527"></a>00527 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00528"></a>00528 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00529"></a>00529 ) |
| <a name="l00530"></a>00530 RETURNS VOID AS $$ |
| <a name="l00531"></a>00531 BEGIN |
| <a name="l00532"></a>00532 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00533"></a>00533 source_table, |
| <a name="l00534"></a>00534 out_table, |
| <a name="l00535"></a>00535 dependent_variable, |
| <a name="l00536"></a>00536 independent_variable, |
| <a name="l00537"></a>00537 grouping_cols, |
| <a name="l00538"></a>00538 NULL, |
| <a name="l00539"></a>00539 20, |
| <a name="l00540"></a>00540 'irls<span class="stringliteral">',</span> |
| <a name="l00541"></a>00541 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00542"></a>00542 <span class="stringliteral"> False);</span> |
| <a name="l00543"></a>00543 <span class="stringliteral">END;</span> |
| <a name="l00544"></a>00544 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00545"></a>00545 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00546"></a>00546 <span class="comment">/**</span> |
| <a name="l00547"></a>00547 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00548"></a>00548 <span class="comment"> **/</span> |
| <a name="l00549"></a>00549 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00550"></a>00550 source_table VARCHAR -- name of input table |
| <a name="l00551"></a>00551 , out_table VARCHAR -- name of output table |
| <a name="l00552"></a>00552 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00553"></a>00553 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00554"></a>00554 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00555"></a>00555 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00556"></a>00556 ) |
| <a name="l00557"></a>00557 RETURNS VOID AS $$ |
| <a name="l00558"></a>00558 BEGIN |
| <a name="l00559"></a>00559 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00560"></a>00560 source_table, |
| <a name="l00561"></a>00561 out_table, |
| <a name="l00562"></a>00562 dependent_variable, |
| <a name="l00563"></a>00563 independent_variable, |
| <a name="l00564"></a>00564 grouping_cols, |
| <a name="l00565"></a>00565 marginal_vars, |
| <a name="l00566"></a>00566 20, |
| <a name="l00567"></a>00567 'irls<span class="stringliteral">',</span> |
| <a name="l00568"></a>00568 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00569"></a>00569 <span class="stringliteral"> False);</span> |
| <a name="l00570"></a>00570 <span class="stringliteral">END;</span> |
| <a name="l00571"></a>00571 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00572"></a>00572 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00573"></a>00573 <span class="comment">/**</span> |
| <a name="l00574"></a>00574 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00575"></a>00575 <span class="comment"> **/</span> |
| <a name="l00576"></a>00576 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00577"></a>00577 source_table VARCHAR -- name of input table |
| <a name="l00578"></a>00578 , out_table VARCHAR -- name of output table |
| <a name="l00579"></a>00579 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00580"></a>00580 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00581"></a>00581 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00582"></a>00582 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00583"></a>00583 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l00584"></a>00584 ) |
| <a name="l00585"></a>00585 RETURNS VOID AS $$ |
| <a name="l00586"></a>00586 BEGIN |
| <a name="l00587"></a>00587 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00588"></a>00588 source_table, |
| <a name="l00589"></a>00589 out_table, |
| <a name="l00590"></a>00590 dependent_variable, |
| <a name="l00591"></a>00591 independent_variable, |
| <a name="l00592"></a>00592 grouping_cols, |
| <a name="l00593"></a>00593 marginal_vars, |
| <a name="l00594"></a>00594 max_iter, |
| <a name="l00595"></a>00595 'irls<span class="stringliteral">',</span> |
| <a name="l00596"></a>00596 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00597"></a>00597 <span class="stringliteral"> False);</span> |
| <a name="l00598"></a>00598 <span class="stringliteral">END;</span> |
| <a name="l00599"></a>00599 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00600"></a>00600 <span class="stringliteral"></span> |
| <a name="l00601"></a>00601 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00602"></a>00602 <span class="comment">/**</span> |
| <a name="l00603"></a>00603 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00604"></a>00604 <span class="comment"> **/</span> |
| <a name="l00605"></a>00605 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00606"></a>00606 source_table VARCHAR -- name of input table |
| <a name="l00607"></a>00607 , out_table VARCHAR -- name of output table |
| <a name="l00608"></a>00608 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00609"></a>00609 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00610"></a>00610 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00611"></a>00611 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00612"></a>00612 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l00613"></a>00613 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l00614"></a>00614 ) |
| <a name="l00615"></a>00615 RETURNS VOID AS $$ |
| <a name="l00616"></a>00616 BEGIN |
| <a name="l00617"></a>00617 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00618"></a>00618 source_table, |
| <a name="l00619"></a>00619 out_table, |
| <a name="l00620"></a>00620 dependent_variable, |
| <a name="l00621"></a>00621 independent_variable, |
| <a name="l00622"></a>00622 grouping_cols, |
| <a name="l00623"></a>00623 marginal_vars, |
| <a name="l00624"></a>00624 max_iter, |
| <a name="l00625"></a>00625 optimizer, |
| <a name="l00626"></a>00626 0.0001, |
| <a name="l00627"></a>00627 False); |
| <a name="l00628"></a>00628 END; |
| <a name="l00629"></a>00629 $$ LANGUAGE plpgsql VOLATILE; |
| <a name="l00630"></a>00630 <span class="comment"></span> |
| <a name="l00631"></a>00631 <span class="comment">/**</span> |
| <a name="l00632"></a>00632 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00633"></a>00633 <span class="comment"> **/</span> |
| <a name="l00634"></a>00634 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_logregr( |
| <a name="l00635"></a>00635 source_table VARCHAR -- name of input table |
| <a name="l00636"></a>00636 , out_table VARCHAR -- name of output table |
| <a name="l00637"></a>00637 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00638"></a>00638 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00639"></a>00639 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00640"></a>00640 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00641"></a>00641 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l00642"></a>00642 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l00643"></a>00643 , tolerance DOUBLE PRECISION -- Tolerance |
| <a name="l00644"></a>00644 ) |
| <a name="l00645"></a>00645 RETURNS VOID AS $$ |
| <a name="l00646"></a>00646 BEGIN |
| <a name="l00647"></a>00647 PERFORM MADLIB_SCHEMA.margins_logregr( |
| <a name="l00648"></a>00648 source_table, |
| <a name="l00649"></a>00649 out_table, |
| <a name="l00650"></a>00650 dependent_variable, |
| <a name="l00651"></a>00651 independent_variable, |
| <a name="l00652"></a>00652 grouping_cols, |
| <a name="l00653"></a>00653 marginal_vars, |
| <a name="l00654"></a>00654 max_iter, |
| <a name="l00655"></a>00655 optimizer, |
| <a name="l00656"></a>00656 tolerance, |
| <a name="l00657"></a>00657 False); |
| <a name="l00658"></a>00658 END; |
| <a name="l00659"></a>00659 $$ LANGUAGE plpgsql VOLATILE; |
| <a name="l00660"></a>00660 -- End of Default Variable calls for margins_logregr |
| <a name="l00661"></a>00661 ------------------------------------------------------------------------------ |
| <a name="l00662"></a>00662 |
| <a name="l00663"></a>00663 |
| <a name="l00664"></a>00664 |
| <a name="l00665"></a>00665 ------------------ Marginal Multi-Logistic Regression ------------------------------ |
| <a name="l00666"></a>00666 |
| <a name="l00667"></a>00667 CREATE TYPE MADLIB_SCHEMA.marginal_mlogregr_result AS ( |
| <a name="l00668"></a>00668 margins DOUBLE PRECISION[], |
| <a name="l00669"></a>00669 coef DOUBLE PRECISION[], |
| <a name="l00670"></a>00670 std_err DOUBLE PRECISION[], |
| <a name="l00671"></a>00671 t_stats DOUBLE PRECISION[], |
| <a name="l00672"></a>00672 p_values DOUBLE PRECISION[] |
| <a name="l00673"></a>00673 ); |
| <a name="l00674"></a>00674 |
| <a name="l00675"></a>00675 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.mlogregr_marginal_step_transition( |
| <a name="l00676"></a>00676 state DOUBLE PRECISION[], |
| <a name="l00677"></a>00677 y INTEGER, |
| <a name="l00678"></a>00678 num_categories INTEGER, |
| <a name="l00679"></a>00679 ref_category INTEGER, |
| <a name="l00680"></a>00680 x DOUBLE PRECISION[], |
| <a name="l00681"></a>00681 coef DOUBLE PRECISION[]) |
| <a name="l00682"></a>00682 RETURNS DOUBLE PRECISION[] |
| <a name="l00683"></a>00683 AS 'MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00684"></a>00684 <span class="stringliteral">LANGUAGE C IMMUTABLE;</span> |
| <a name="l00685"></a>00685 <span class="stringliteral"></span> |
| <a name="l00686"></a>00686 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.mlogregr_marginal_step_merge_states(</span> |
| <a name="l00687"></a>00687 <span class="stringliteral"> state1 DOUBLE PRECISION[],</span> |
| <a name="l00688"></a>00688 <span class="stringliteral"> state2 DOUBLE PRECISION[])</span> |
| <a name="l00689"></a>00689 <span class="stringliteral">RETURNS DOUBLE PRECISION[]</span> |
| <a name="l00690"></a>00690 <span class="stringliteral">AS '</span>MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00691"></a>00691 <span class="stringliteral">LANGUAGE C IMMUTABLE STRICT;</span> |
| <a name="l00692"></a>00692 <span class="stringliteral"></span> |
| <a name="l00693"></a>00693 <span class="stringliteral"></span> |
| <a name="l00694"></a>00694 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.mlogregr_marginal_step_final(</span> |
| <a name="l00695"></a>00695 <span class="stringliteral"> state DOUBLE PRECISION[])</span> |
| <a name="l00696"></a>00696 <span class="stringliteral">RETURNS MADLIB_SCHEMA.marginal_mlogregr_result</span> |
| <a name="l00697"></a>00697 <span class="stringliteral">AS '</span>MODULE_PATHNAME<span class="stringliteral">'</span> |
| <a name="l00698"></a>00698 <span class="stringliteral">LANGUAGE C IMMUTABLE STRICT;</span> |
| <a name="l00699"></a>00699 <span class="stringliteral"></span> |
| <a name="l00700"></a>00700 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00701"></a>00701 <span class="comment">/**</span> |
| <a name="l00702"></a>00702 <span class="comment"> * @brief Compute marginal effects for multinomial logistic regression.</span> |
| <a name="l00703"></a>00703 <span class="comment"> *</span> |
| <a name="l00704"></a>00704 <span class="comment"> * @param dependentVariable Column containing the dependent variable</span> |
| <a name="l00705"></a>00705 <span class="comment"> * @param independentVariables Column containing the array of independent variables</span> |
| <a name="l00706"></a>00706 <span class="comment"> * @param num_categories Number of categories</span> |
| <a name="l00707"></a>00707 <span class="comment"> * @param ref_category Reference category</span> |
| <a name="l00708"></a>00708 <span class="comment"> * @param coef Column containing the array of the coefficients (as obtained by mlogregr)</span> |
| <a name="l00709"></a>00709 <span class="comment"> *</span> |
| <a name="l00710"></a>00710 <span class="comment"> * @par</span> |
| <a name="l00711"></a>00711 <span class="comment"> * To include an intercept in the model, set one coordinate in the</span> |
| <a name="l00712"></a>00712 <span class="comment"> * <tt>independentVariables</tt> array to 1.</span> |
| <a name="l00713"></a>00713 <span class="comment"> *</span> |
| <a name="l00714"></a>00714 <span class="comment"> * @return A composite value:</span> |
| <a name="l00715"></a>00715 <span class="comment"> * - <tt>margins FLOAT8[] </tt> - Array of marginal effects</span> |
| <a name="l00716"></a>00716 <span class="comment"> * - <tt>coef FLOAT8[] </tt> - The coefficients for the regression</span> |
| <a name="l00717"></a>00717 <span class="comment"> * - <tt>std_err FLOAT8[]</tt> - Array of standard-errors (using the delta method),</span> |
| <a name="l00718"></a>00718 <span class="comment"> * - <tt>t_stats FLOAT8[]</tt> - Array of t-statistics</span> |
| <a name="l00719"></a>00719 <span class="comment"> * - <tt>p_values FLOAT8[]</tt> - Array of p-values</span> |
| <a name="l00720"></a>00720 <span class="comment"> *</span> |
| <a name="l00721"></a>00721 <span class="comment"> * @usage</span> |
| <a name="l00722"></a>00722 <span class="comment"> * - Get all the diagnostic statistics:\n</span> |
| <a name="l00723"></a>00723 <span class="comment"> *</span> |
| <a name="l00724"></a>00724 <span class="comment"> * <pre> SELECT marginal_mlogregr(<em>dependentVariable</em>,</span> |
| <a name="l00725"></a>00725 <span class="comment"> * <em>independentVariables</em>, coef)</span> |
| <a name="l00726"></a>00726 <span class="comment"> * FROM <em>dataTable</em>;</span> |
| <a name="l00727"></a>00727 <span class="comment"> * </pre></span> |
| <a name="l00728"></a>00728 <span class="comment"> */</span> |
| <a name="l00729"></a>00729 |
| <a name="l00730"></a>00730 CREATE AGGREGATE MADLIB_SCHEMA.marginal_mlogregr( |
| <a name="l00731"></a>00731 /*+ "dependentVariable" */ INTEGER, |
| <a name="l00732"></a>00732 /*+ "num_categories" */ INTEGER, |
| <a name="l00733"></a>00733 /*+ "ref_category" */ INTEGER, |
| <a name="l00734"></a>00734 /*+ "independentVariables" */ DOUBLE PRECISION[], |
| <a name="l00735"></a>00735 /*+ "coef" */ DOUBLE PRECISION[] )( |
| <a name="l00736"></a>00736 STYPE=DOUBLE PRECISION[], |
| <a name="l00737"></a>00737 SFUNC=MADLIB_SCHEMA.mlogregr_marginal_step_transition, |
| <a name="l00738"></a>00738 m4_ifdef(`__GREENPLUM__',`PREFUNC=MADLIB_SCHEMA.mlogregr_marginal_step_merge_states,<span class="stringliteral">')</span> |
| <a name="l00739"></a>00739 <span class="stringliteral"> FINALFUNC=MADLIB_SCHEMA.mlogregr_marginal_step_final,</span> |
| <a name="l00740"></a>00740 <span class="stringliteral"> INITCOND='</span>{0,0,0,0,0,0}<span class="stringliteral">'</span> |
| <a name="l00741"></a>00741 <span class="stringliteral">);</span> |
| <a name="l00742"></a>00742 <span class="stringliteral"></span> |
| <a name="l00743"></a>00743 <span class="stringliteral"></span> |
| <a name="l00744"></a>00744 <span class="stringliteral">--------------------------- Interface ----------------------------------</span> |
| <a name="l00745"></a>00745 <span class="stringliteral"></span> |
| <a name="l00746"></a>00746 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr(</span> |
| <a name="l00747"></a>00747 <span class="stringliteral"> usage_string VARCHAR -- usage string</span> |
| <a name="l00748"></a>00748 <span class="stringliteral">)</span> |
| <a name="l00749"></a>00749 <span class="stringliteral">RETURNS VARCHAR AS $$</span> |
| <a name="l00750"></a>00750 <span class="stringliteral">DECLARE</span> |
| <a name="l00751"></a>00751 <span class="stringliteral">insert_string VARCHAR;</span> |
| <a name="l00752"></a>00752 <span class="stringliteral">BEGIN</span> |
| <a name="l00753"></a>00753 <span class="stringliteral"> IF (usage_string = '</span><span class="stringliteral">' OR usage_string = '</span>help<span class="stringliteral">' OR usage_string = '</span>?<span class="stringliteral">') THEN</span> |
| <a name="l00754"></a>00754 <span class="stringliteral"> insert_string := '</span><span class="stringliteral">' ||</span> |
| <a name="l00755"></a>00755 <span class="stringliteral"> E'</span>Summary \n<span class="stringliteral">' ||</span> |
| <a name="l00756"></a>00756 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00757"></a>00757 <span class="stringliteral"> E'</span> Functionality: Calculate marginal effects <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression\n<span class="stringliteral">' ||</span> |
| <a name="l00758"></a>00758 <span class="stringliteral"> E'</span> The funciton first runs the regression and then calculates the \n<span class="stringliteral">' ||</span> |
| <a name="l00759"></a>00759 <span class="stringliteral"> E'</span> coefficients and uses them to calculate the marginal effects \n<span class="stringliteral">' ||</span> |
| <a name="l00760"></a>00760 <span class="stringliteral"> E'</span> SELECT {schema_madlib}.margins_mlogregr(<span class="stringliteral">''</span>source_table<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00761"></a>00761 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>output_table<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00762"></a>00762 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>dependent_variable<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00763"></a>00763 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>independent_variable<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00764"></a>00764 <span class="stringliteral"> E'</span> [, ref_category \n<span class="stringliteral">' ||</span> |
| <a name="l00765"></a>00765 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>grouping_cols<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00766"></a>00766 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>marginal_variables<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00767"></a>00767 <span class="stringliteral"> E'</span> , max_iter \n<span class="stringliteral">' ||</span> |
| <a name="l00768"></a>00768 <span class="stringliteral"> E'</span> ,<span class="stringliteral">''</span>optimizer<span class="stringliteral">''</span> \n<span class="stringliteral">' ||</span> |
| <a name="l00769"></a>00769 <span class="stringliteral"> E'</span> , tolerance \n<span class="stringliteral">' ||</span> |
| <a name="l00770"></a>00770 <span class="stringliteral"> E'</span> , verbose_mode \n<span class="stringliteral">' ||</span> |
| <a name="l00771"></a>00771 <span class="stringliteral"> E'</span> ]<span class="stringliteral">' ||</span> |
| <a name="l00772"></a>00772 <span class="stringliteral"> E'</span> );\n<span class="stringliteral">' ||</span> |
| <a name="l00773"></a>00773 <span class="stringliteral"> E'</span>For more details on <span class="keyword">function</span> usage: \n<span class="stringliteral">' ||</span> |
| <a name="l00774"></a>00774 <span class="stringliteral"> E'</span>SELECT {schema_madlib}.margins_mlogregr(<span class="stringliteral">''</span>usage<span class="stringliteral">''</span>) \n<span class="stringliteral">' ||</span> |
| <a name="l00775"></a>00775 <span class="stringliteral"> E'</span><span class="stringliteral">';</span> |
| <a name="l00776"></a>00776 <span class="stringliteral"> ElSIF (usage_string = '</span>usage<span class="stringliteral">') THEN</span> |
| <a name="l00777"></a>00777 <span class="stringliteral"> insert_string := '</span><span class="stringliteral">' ||</span> |
| <a name="l00778"></a>00778 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00779"></a>00779 <span class="stringliteral"> E'</span>Usage\n<span class="stringliteral">' ||</span> |
| <a name="l00780"></a>00780 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00781"></a>00781 <span class="stringliteral"> E'</span> SELECT {schema_madlib}.margins_mlogregr( \n<span class="stringliteral">' ||</span> |
| <a name="l00782"></a>00782 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>source_table<span class="stringliteral">''</span>, -- Name of data table \n<span class="stringliteral">' ||</span> |
| <a name="l00783"></a>00783 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>output_table<span class="stringliteral">''</span>, -- Name of result table (overwrites <span class="keywordflow">if</span> exists) \n<span class="stringliteral">' ||</span> |
| <a name="l00784"></a>00784 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>dependent_variable<span class="stringliteral">''</span>, -- Name of column <span class="keywordflow">for</span> dependent variables\n<span class="stringliteral">' ||</span> |
| <a name="l00785"></a>00785 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>independent_variable<span class="stringliteral">''</span>, -- Name of column <span class="keywordflow">for</span> independent variables\n<span class="stringliteral">' ||</span> |
| <a name="l00786"></a>00786 <span class="stringliteral"> E'</span> (can be any SQL expression that evaluates to an array)\n<span class="stringliteral">' ||</span> |
| <a name="l00787"></a>00787 <span class="stringliteral"> E'</span>[ ref_category, -- Reference category <span class="keywordflow">for</span> the multinomial logisitic regressionby\n<span class="stringliteral">' ||</span> |
| <a name="l00788"></a>00788 <span class="stringliteral"> E'</span> (Optional : Default 0) \n<span class="stringliteral">' ||</span> |
| <a name="l00789"></a>00789 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>group_cols<span class="stringliteral">''</span>, -- Comma separated <span class="keywordtype">string</span> with columns to group by\n<span class="stringliteral">' ||</span> |
| <a name="l00790"></a>00790 <span class="stringliteral"> E'</span> (Optional : Default NULL => no grouping) \n<span class="stringliteral">' ||</span> |
| <a name="l00791"></a>00791 <span class="stringliteral"> E'</span> margins_vars, -- Index list (base 1) representing the independent variables to compute marginal effects on \n<span class="stringliteral">' ||</span> |
| <a name="l00792"></a>00792 <span class="stringliteral"> E'</span> (Optional : Default NULL which computes marginal effects on all variables) \n<span class="stringliteral">' ||</span> |
| <a name="l00793"></a>00793 <span class="stringliteral"> E'</span> max_iter, -- Maximum number of iterations <span class="keywordflow">for</span> the <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression\n<span class="stringliteral">' ||</span> |
| <a name="l00794"></a>00794 <span class="stringliteral"> E'</span> (Optional : Default 20) \n<span class="stringliteral">' ||</span> |
| <a name="l00795"></a>00795 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>optimizer<span class="stringliteral">''</span>, -- Optimizer <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression (newton/irls, cg or igd)\n<span class="stringliteral">' ||</span> |
| <a name="l00796"></a>00796 <span class="stringliteral"> E'</span> (Optional : Default irls) \n<span class="stringliteral">' ||</span> |
| <a name="l00797"></a>00797 <span class="stringliteral"> E'</span> tolerance, -- Termination criterion <span class="keywordflow">for</span> <a class="code" href="logistic_8sql__in.html#a4ded9be5c8b111dbb3109efaad83d69e" title="Evaluate the usual logistic function in an under-/overflow-safe way.">logistic</a> regression (relative)\n<span class="stringliteral">' ||</span> |
| <a name="l00798"></a>00798 <span class="stringliteral"> E'</span> (Optional : Default 1e-4) \n<span class="stringliteral">' ||</span> |
| <a name="l00799"></a>00799 <span class="stringliteral"> E'</span> verbose_mode, -- Verbose mode \n<span class="stringliteral">' ||</span> |
| <a name="l00800"></a>00800 <span class="stringliteral"> E'</span> (Optional : Default False) \n<span class="stringliteral">' ||</span> |
| <a name="l00801"></a>00801 <span class="stringliteral"> E'</span>]<span class="stringliteral">' ||</span> |
| <a name="l00802"></a>00802 <span class="stringliteral"> E'</span> );\n<span class="stringliteral">' ||</span> |
| <a name="l00803"></a>00803 <span class="stringliteral"> E'</span>\n<span class="stringliteral">' ||</span> |
| <a name="l00804"></a>00804 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00805"></a>00805 <span class="stringliteral"> E'</span>Output:\n<span class="stringliteral">' ||</span> |
| <a name="l00806"></a>00806 <span class="stringliteral"> E'</span>-----------------------------------------------------------------------------------------\n<span class="stringliteral">' ||</span> |
| <a name="l00807"></a>00807 <span class="stringliteral"> E'</span> The output table (<span class="stringliteral">''</span>output_table<span class="stringliteral">''</span> above) has the following columns\n<span class="stringliteral">' ||</span> |
| <a name="l00808"></a>00808 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>margins<span class="stringliteral">''</span> DOUBLE PRECISION[], -- Marginal effects \n<span class="stringliteral">' ||</span> |
| <a name="l00809"></a>00809 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>std_err<span class="stringliteral">''</span> DOUBLE PRECISION[], -- Standard errors <span class="keyword">using</span> the delta method\n<span class="stringliteral">' ||</span> |
| <a name="l00810"></a>00810 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>t_stats<span class="stringliteral">''</span> DOUBLE PRECISION[], -- T-stats of the standard errors\n<span class="stringliteral">' ||</span> |
| <a name="l00811"></a>00811 <span class="stringliteral"> E'</span> <span class="stringliteral">''</span>p_values<span class="stringliteral">''</span> DOUBLE PRECISION[], -- p-values of the standard errors\n<span class="stringliteral">' ||</span> |
| <a name="l00812"></a>00812 <span class="stringliteral"> E'</span>\n<span class="stringliteral">' ||</span> |
| <a name="l00813"></a>00813 <span class="stringliteral"> E'</span><span class="stringliteral">';</span> |
| <a name="l00814"></a>00814 <span class="stringliteral"> ELSE</span> |
| <a name="l00815"></a>00815 <span class="stringliteral"> insert_string := '</span>No such option. Run SELECT {schema_madlib}.margins_mlogregr()<span class="stringliteral">';</span> |
| <a name="l00816"></a>00816 <span class="stringliteral"> END IF;</span> |
| <a name="l00817"></a>00817 <span class="stringliteral"> RETURN insert_string;</span> |
| <a name="l00818"></a>00818 <span class="stringliteral">END;</span> |
| <a name="l00819"></a>00819 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00820"></a>00820 <span class="stringliteral"></span> |
| <a name="l00821"></a>00821 <span class="stringliteral">CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr()</span> |
| <a name="l00822"></a>00822 <span class="stringliteral">RETURNS VARCHAR AS $$</span> |
| <a name="l00823"></a>00823 <span class="stringliteral">BEGIN</span> |
| <a name="l00824"></a>00824 <span class="stringliteral"> RETURN MADLIB_SCHEMA.margins_mlogregr('</span><span class="stringliteral">');</span> |
| <a name="l00825"></a>00825 <span class="stringliteral">END;</span> |
| <a name="l00826"></a>00826 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00827"></a>00827 <span class="stringliteral"></span> |
| <a name="l00828"></a>00828 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00829"></a>00829 <span class="comment">/**</span> |
| <a name="l00830"></a>00830 <span class="comment"> @brief A wrapper function for the various marginal multinomial regression</span> |
| <a name="l00831"></a>00831 <span class="comment"> *</span> |
| <a name="l00832"></a>00832 <span class="comment"> * @param source_table String identifying the input table</span> |
| <a name="l00833"></a>00833 <span class="comment"> * @param out_table String identifying the output table to be created</span> |
| <a name="l00834"></a>00834 <span class="comment"> * @param dependent_varname Column containing the dependent variable</span> |
| <a name="l00835"></a>00835 <span class="comment"> * @param input_independent_varname Column containing the array of independent variables</span> |
| <a name="l00836"></a>00836 <span class="comment"> * @param ref_category Reference category for the multinomial logistic regression</span> |
| <a name="l00837"></a>00837 <span class="comment"> * @param grouping_cols Set of columns to group by.</span> |
| <a name="l00838"></a>00838 <span class="comment"> * @param marginal_vars Subset of independent variables to calculate marginal effects for.</span> |
| <a name="l00839"></a>00839 <span class="comment"> * @param max_iter Maximum number of iterations</span> |
| <a name="l00840"></a>00840 <span class="comment"> * @param optimzer Optimizer to be used (newton/irls, cg or idg)</span> |
| <a name="l00841"></a>00841 <span class="comment"> * @param tolerance Resiual tolerance</span> |
| <a name="l00842"></a>00842 <span class="comment"> * @param verbose_mode Verbose mode (on/off)</span> |
| <a name="l00843"></a>00843 <span class="comment"> *</span> |
| <a name="l00844"></a>00844 <span class="comment"> * @par</span> |
| <a name="l00845"></a>00845 <span class="comment"> * To include an intercept in the model, set one coordinate in the</span> |
| <a name="l00846"></a>00846 <span class="comment"> * <tt>independentVariables</tt> array to 1.</span> |
| <a name="l00847"></a>00847 <span class="comment"> *</span> |
| <a name="l00848"></a>00848 <span class="comment"> * @return void</span> |
| <a name="l00849"></a>00849 <span class="comment"> *</span> |
| <a name="l00850"></a>00850 <span class="comment"> * @usage</span> |
| <a name="l00851"></a>00851 <span class="comment"> * For function summary information. Run</span> |
| <a name="l00852"></a>00852 <span class="comment"> * sql> select margins_mlogregr('help');</span> |
| <a name="l00853"></a>00853 <span class="comment"> * OR</span> |
| <a name="l00854"></a>00854 <span class="comment"> * sql> select margins_mlogregr();</span> |
| <a name="l00855"></a>00855 <span class="comment"> * OR</span> |
| <a name="l00856"></a>00856 <span class="comment"> * sql> select margins_mlogregr('?');</span> |
| <a name="l00857"></a>00857 <span class="comment"> * For function usage information. Run</span> |
| <a name="l00858"></a>00858 <span class="comment"> * sql> select margins_mlogregr('usage');</span> |
| <a name="l00859"></a>00859 <span class="comment"> *</span> |
| <a name="l00860"></a>00860 <span class="comment"> */</span> |
| <a name="l00861"></a>00861 |
| <a name="l00862"></a>00862 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00863"></a>00863 source_table VARCHAR -- name of input table |
| <a name="l00864"></a>00864 , out_table VARCHAR -- name of output table |
| <a name="l00865"></a>00865 , dependent_varname VARCHAR -- name of dependent variable |
| <a name="l00866"></a>00866 , input_independent_varname VARCHAR -- name of independent variable |
| <a name="l00867"></a>00867 , ref_category INTEGER -- reference category |
| <a name="l00868"></a>00868 , input_group_cols VARCHAR -- names of columns to group by |
| <a name="l00869"></a>00869 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00870"></a>00870 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l00871"></a>00871 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l00872"></a>00872 , tolerance DOUBLE PRECISION -- Tolerance |
| <a name="l00873"></a>00873 , verbose_mode BOOLEAN -- Verbose mode |
| <a name="l00874"></a>00874 ) |
| <a name="l00875"></a>00875 RETURNS VOID AS $$ |
| <a name="l00876"></a>00876 PythonFunction(regress, marginal, margins_mlogregr) |
| <a name="l00877"></a>00877 $$ LANGUAGE plpythonu; |
| <a name="l00878"></a>00878 |
| <a name="l00879"></a>00879 |
| <a name="l00880"></a>00880 |
| <a name="l00881"></a>00881 -- Default Variable calls for margins_mlogregr |
| <a name="l00882"></a>00882 ------------------------------------------------------------------------------ |
| <a name="l00883"></a>00883 <span class="comment"></span> |
| <a name="l00884"></a>00884 <span class="comment">/**</span> |
| <a name="l00885"></a>00885 <span class="comment"> * @brief Marginal effects with default variables</span> |
| <a name="l00886"></a>00886 <span class="comment"> **/</span> |
| <a name="l00887"></a>00887 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00888"></a>00888 source_table VARCHAR -- name of input table |
| <a name="l00889"></a>00889 , out_table VARCHAR -- name of output table |
| <a name="l00890"></a>00890 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00891"></a>00891 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00892"></a>00892 ) |
| <a name="l00893"></a>00893 RETURNS VOID AS $$ |
| <a name="l00894"></a>00894 BEGIN |
| <a name="l00895"></a>00895 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00896"></a>00896 source_table, |
| <a name="l00897"></a>00897 out_table, |
| <a name="l00898"></a>00898 dependent_variable, |
| <a name="l00899"></a>00899 independent_variable, |
| <a name="l00900"></a>00900 0, |
| <a name="l00901"></a>00901 NULL, |
| <a name="l00902"></a>00902 NULL, |
| <a name="l00903"></a>00903 20, |
| <a name="l00904"></a>00904 'irls<span class="stringliteral">',</span> |
| <a name="l00905"></a>00905 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00906"></a>00906 <span class="stringliteral"> False);</span> |
| <a name="l00907"></a>00907 <span class="stringliteral">END;</span> |
| <a name="l00908"></a>00908 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00909"></a>00909 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00910"></a>00910 <span class="comment">/**</span> |
| <a name="l00911"></a>00911 <span class="comment"> * @brief Marginal effects with default variables</span> |
| <a name="l00912"></a>00912 <span class="comment"> **/</span> |
| <a name="l00913"></a>00913 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00914"></a>00914 source_table VARCHAR -- name of input table |
| <a name="l00915"></a>00915 , out_table VARCHAR -- name of output table |
| <a name="l00916"></a>00916 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00917"></a>00917 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00918"></a>00918 , ref_category INTEGER -- reference category |
| <a name="l00919"></a>00919 ) |
| <a name="l00920"></a>00920 RETURNS VOID AS $$ |
| <a name="l00921"></a>00921 BEGIN |
| <a name="l00922"></a>00922 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00923"></a>00923 source_table, |
| <a name="l00924"></a>00924 out_table, |
| <a name="l00925"></a>00925 dependent_variable, |
| <a name="l00926"></a>00926 independent_variable, |
| <a name="l00927"></a>00927 ref_category, |
| <a name="l00928"></a>00928 NULL, |
| <a name="l00929"></a>00929 NULL, |
| <a name="l00930"></a>00930 20, |
| <a name="l00931"></a>00931 'irls<span class="stringliteral">',</span> |
| <a name="l00932"></a>00932 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00933"></a>00933 <span class="stringliteral"> False);</span> |
| <a name="l00934"></a>00934 <span class="stringliteral">END;</span> |
| <a name="l00935"></a>00935 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00936"></a>00936 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00937"></a>00937 <span class="comment">/**</span> |
| <a name="l00938"></a>00938 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00939"></a>00939 <span class="comment"> **/</span> |
| <a name="l00940"></a>00940 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00941"></a>00941 source_table VARCHAR -- name of input table |
| <a name="l00942"></a>00942 , out_table VARCHAR -- name of output table |
| <a name="l00943"></a>00943 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00944"></a>00944 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00945"></a>00945 , ref_category INTEGER -- reference category |
| <a name="l00946"></a>00946 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00947"></a>00947 ) |
| <a name="l00948"></a>00948 RETURNS VOID AS $$ |
| <a name="l00949"></a>00949 BEGIN |
| <a name="l00950"></a>00950 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00951"></a>00951 source_table, |
| <a name="l00952"></a>00952 out_table, |
| <a name="l00953"></a>00953 dependent_variable, |
| <a name="l00954"></a>00954 independent_variable, |
| <a name="l00955"></a>00955 ref_category, |
| <a name="l00956"></a>00956 grouping_cols, |
| <a name="l00957"></a>00957 NULL, |
| <a name="l00958"></a>00958 20, |
| <a name="l00959"></a>00959 'irls<span class="stringliteral">',</span> |
| <a name="l00960"></a>00960 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00961"></a>00961 <span class="stringliteral"> False);</span> |
| <a name="l00962"></a>00962 <span class="stringliteral">END;</span> |
| <a name="l00963"></a>00963 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00964"></a>00964 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00965"></a>00965 <span class="comment">/**</span> |
| <a name="l00966"></a>00966 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00967"></a>00967 <span class="comment"> **/</span> |
| <a name="l00968"></a>00968 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00969"></a>00969 source_table VARCHAR -- name of input table |
| <a name="l00970"></a>00970 , out_table VARCHAR -- name of output table |
| <a name="l00971"></a>00971 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l00972"></a>00972 , independent_variable VARCHAR -- name of independent variable |
| <a name="l00973"></a>00973 , ref_category INTEGER -- reference category |
| <a name="l00974"></a>00974 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l00975"></a>00975 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l00976"></a>00976 ) |
| <a name="l00977"></a>00977 RETURNS VOID AS $$ |
| <a name="l00978"></a>00978 BEGIN |
| <a name="l00979"></a>00979 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00980"></a>00980 source_table, |
| <a name="l00981"></a>00981 out_table, |
| <a name="l00982"></a>00982 dependent_variable, |
| <a name="l00983"></a>00983 independent_variable, |
| <a name="l00984"></a>00984 ref_category, |
| <a name="l00985"></a>00985 grouping_cols, |
| <a name="l00986"></a>00986 marginal_vars, |
| <a name="l00987"></a>00987 20, |
| <a name="l00988"></a>00988 'irls<span class="stringliteral">',</span> |
| <a name="l00989"></a>00989 <span class="stringliteral"> 0.0001,</span> |
| <a name="l00990"></a>00990 <span class="stringliteral"> False);</span> |
| <a name="l00991"></a>00991 <span class="stringliteral">END;</span> |
| <a name="l00992"></a>00992 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l00993"></a>00993 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l00994"></a>00994 <span class="comment">/**</span> |
| <a name="l00995"></a>00995 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l00996"></a>00996 <span class="comment"> **/</span> |
| <a name="l00997"></a>00997 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l00998"></a>00998 source_table VARCHAR -- name of input table |
| <a name="l00999"></a>00999 , out_table VARCHAR -- name of output table |
| <a name="l01000"></a>01000 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l01001"></a>01001 , independent_variable VARCHAR -- name of independent variable |
| <a name="l01002"></a>01002 , ref_category INTEGER -- reference category |
| <a name="l01003"></a>01003 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l01004"></a>01004 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l01005"></a>01005 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l01006"></a>01006 ) |
| <a name="l01007"></a>01007 RETURNS VOID AS $$ |
| <a name="l01008"></a>01008 BEGIN |
| <a name="l01009"></a>01009 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l01010"></a>01010 source_table, |
| <a name="l01011"></a>01011 out_table, |
| <a name="l01012"></a>01012 dependent_variable, |
| <a name="l01013"></a>01013 independent_variable, |
| <a name="l01014"></a>01014 ref_category, |
| <a name="l01015"></a>01015 grouping_cols, |
| <a name="l01016"></a>01016 marginal_vars, |
| <a name="l01017"></a>01017 max_iter, |
| <a name="l01018"></a>01018 'irls<span class="stringliteral">',</span> |
| <a name="l01019"></a>01019 <span class="stringliteral"> 0.0001,</span> |
| <a name="l01020"></a>01020 <span class="stringliteral"> False);</span> |
| <a name="l01021"></a>01021 <span class="stringliteral">END;</span> |
| <a name="l01022"></a>01022 <span class="stringliteral">$$ LANGUAGE plpgsql VOLATILE;</span> |
| <a name="l01023"></a>01023 <span class="stringliteral"></span> |
| <a name="l01024"></a>01024 <span class="stringliteral"></span><span class="comment"></span> |
| <a name="l01025"></a>01025 <span class="comment">/**</span> |
| <a name="l01026"></a>01026 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l01027"></a>01027 <span class="comment"> **/</span> |
| <a name="l01028"></a>01028 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l01029"></a>01029 source_table VARCHAR -- name of input table |
| <a name="l01030"></a>01030 , out_table VARCHAR -- name of output table |
| <a name="l01031"></a>01031 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l01032"></a>01032 , independent_variable VARCHAR -- name of independent variable |
| <a name="l01033"></a>01033 , ref_category INTEGER -- reference category |
| <a name="l01034"></a>01034 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l01035"></a>01035 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l01036"></a>01036 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l01037"></a>01037 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l01038"></a>01038 ) |
| <a name="l01039"></a>01039 RETURNS VOID AS $$ |
| <a name="l01040"></a>01040 BEGIN |
| <a name="l01041"></a>01041 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l01042"></a>01042 source_table, |
| <a name="l01043"></a>01043 out_table, |
| <a name="l01044"></a>01044 dependent_variable, |
| <a name="l01045"></a>01045 independent_variable, |
| <a name="l01046"></a>01046 ref_category, |
| <a name="l01047"></a>01047 grouping_cols, |
| <a name="l01048"></a>01048 marginal_vars, |
| <a name="l01049"></a>01049 max_iter, |
| <a name="l01050"></a>01050 optimizer, |
| <a name="l01051"></a>01051 0.0001, |
| <a name="l01052"></a>01052 False); |
| <a name="l01053"></a>01053 END; |
| <a name="l01054"></a>01054 $$ LANGUAGE plpgsql VOLATILE; |
| <a name="l01055"></a>01055 <span class="comment"></span> |
| <a name="l01056"></a>01056 <span class="comment">/**</span> |
| <a name="l01057"></a>01057 <span class="comment"> * @brief Marginal effects with default variable_names</span> |
| <a name="l01058"></a>01058 <span class="comment"> **/</span> |
| <a name="l01059"></a>01059 CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l01060"></a>01060 source_table VARCHAR -- name of input table |
| <a name="l01061"></a>01061 , out_table VARCHAR -- name of output table |
| <a name="l01062"></a>01062 , dependent_variable VARCHAR -- name of dependent variable |
| <a name="l01063"></a>01063 , independent_variable VARCHAR -- name of independent variable |
| <a name="l01064"></a>01064 , ref_category INTEGER -- reference category |
| <a name="l01065"></a>01065 , grouping_cols VARCHAR -- name of grouping cols |
| <a name="l01066"></a>01066 , marginal_vars INTEGER[] -- indices of variables to calculate marginal effects on |
| <a name="l01067"></a>01067 , max_iter INTEGER -- Max iterations for the logstic regression inner call |
| <a name="l01068"></a>01068 , optimizer VARCHAR -- Logistic regression optimizer |
| <a name="l01069"></a>01069 , tolerance DOUBLE PRECISION -- Tolerance |
| <a name="l01070"></a>01070 ) |
| <a name="l01071"></a>01071 RETURNS VOID AS $$ |
| <a name="l01072"></a>01072 BEGIN |
| <a name="l01073"></a>01073 PERFORM MADLIB_SCHEMA.margins_mlogregr( |
| <a name="l01074"></a>01074 source_table, |
| <a name="l01075"></a>01075 out_table, |
| <a name="l01076"></a>01076 dependent_variable, |
| <a name="l01077"></a>01077 independent_variable, |
| <a name="l01078"></a>01078 ref_category, |
| <a name="l01079"></a>01079 grouping_cols, |
| <a name="l01080"></a>01080 marginal_vars, |
| <a name="l01081"></a>01081 max_iter, |
| <a name="l01082"></a>01082 optimizer, |
| <a name="l01083"></a>01083 tolerance, |
| <a name="l01084"></a>01084 False); |
| <a name="l01085"></a>01085 END; |
| <a name="l01086"></a>01086 $$ LANGUAGE plpgsql VOLATILE; |
| <a name="l01087"></a>01087 -- End of Default Variable calls for margins_mlogregr |
| <a name="l01088"></a>01088 ------------------------------------------------------------------------------ |
| </pre></div></div> |
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