| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| package org.apache.commons.math.distribution; |
| |
| import java.io.Serializable; |
| |
| import org.apache.commons.math.MathException; |
| import org.apache.commons.math.MaxIterationsExceededException; |
| import org.apache.commons.math.special.Erf; |
| |
| /** |
| * Default implementation of |
| * {@link org.apache.commons.math.distribution.NormalDistribution}. |
| * |
| * @version $Revision$ $Date$ |
| */ |
| public class NormalDistributionImpl extends AbstractContinuousDistribution |
| implements NormalDistribution, Serializable { |
| |
| /** Serializable version identifier */ |
| private static final long serialVersionUID = 8589540077390120676L; |
| |
| /** The mean of this distribution. */ |
| private double mean = 0; |
| |
| /** The standard deviation of this distribution. */ |
| private double standardDeviation = 1; |
| |
| /** |
| * Create a normal distribution using the given mean and standard deviation. |
| * @param mean mean for this distribution |
| * @param sd standard deviation for this distribution |
| */ |
| public NormalDistributionImpl(double mean, double sd){ |
| super(); |
| setMean(mean); |
| setStandardDeviation(sd); |
| } |
| |
| /** |
| * Creates normal distribution with the mean equal to zero and standard |
| * deviation equal to one. |
| */ |
| public NormalDistributionImpl(){ |
| this(0.0, 1.0); |
| } |
| |
| /** |
| * Access the mean. |
| * @return mean for this distribution |
| */ |
| public double getMean() { |
| return mean; |
| } |
| |
| /** |
| * Modify the mean. |
| * @param mean for this distribution |
| */ |
| public void setMean(double mean) { |
| this.mean = mean; |
| } |
| |
| /** |
| * Access the standard deviation. |
| * @return standard deviation for this distribution |
| */ |
| public double getStandardDeviation() { |
| return standardDeviation; |
| } |
| |
| /** |
| * Modify the standard deviation. |
| * @param sd standard deviation for this distribution |
| * @throws IllegalArgumentException if <code>sd</code> is not positive. |
| */ |
| public void setStandardDeviation(double sd) { |
| if (sd <= 0.0) { |
| throw new IllegalArgumentException( |
| "Standard deviation must be positive."); |
| } |
| standardDeviation = sd; |
| } |
| |
| /** |
| * For this distribution, X, this method returns P(X < <code>x</code>). |
| * @param x the value at which the CDF is evaluated. |
| * @return CDF evaluted at <code>x</code>. |
| * @throws MathException if the algorithm fails to converge; unless |
| * x is more than 20 standard deviations from the mean, in which case the |
| * convergence exception is caught and 0 or 1 is returned. |
| */ |
| public double cumulativeProbability(double x) throws MathException { |
| try { |
| return 0.5 * (1.0 + Erf.erf((x - mean) / |
| (standardDeviation * Math.sqrt(2.0)))); |
| } catch (MaxIterationsExceededException ex) { |
| if (x < (mean - 20 * standardDeviation)) { // JDK 1.5 blows at 38 |
| return 0.0d; |
| } else if (x > (mean + 20 * standardDeviation)) { |
| return 1.0d; |
| } else { |
| throw ex; |
| } |
| } |
| } |
| |
| /** |
| * For this distribution, X, this method returns the critical point x, such |
| * that P(X < x) = <code>p</code>. |
| * <p> |
| * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and |
| * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> |
| * |
| * @param p the desired probability |
| * @return x, such that P(X < x) = <code>p</code> |
| * @throws MathException if the inverse cumulative probability can not be |
| * computed due to convergence or other numerical errors. |
| * @throws IllegalArgumentException if <code>p</code> is not a valid |
| * probability. |
| */ |
| public double inverseCumulativeProbability(final double p) |
| throws MathException { |
| if (p == 0) { |
| return Double.NEGATIVE_INFINITY; |
| } |
| if (p == 1) { |
| return Double.POSITIVE_INFINITY; |
| } |
| return super.inverseCumulativeProbability(p); |
| } |
| |
| /** |
| * Access the domain value lower bound, based on <code>p</code>, used to |
| * bracket a CDF root. This method is used by |
| * {@link #inverseCumulativeProbability(double)} to find critical values. |
| * |
| * @param p the desired probability for the critical value |
| * @return domain value lower bound, i.e. |
| * P(X < <i>lower bound</i>) < <code>p</code> |
| */ |
| protected double getDomainLowerBound(double p) { |
| double ret; |
| |
| if (p < .5) { |
| ret = -Double.MAX_VALUE; |
| } else { |
| ret = getMean(); |
| } |
| |
| return ret; |
| } |
| |
| /** |
| * Access the domain value upper bound, based on <code>p</code>, used to |
| * bracket a CDF root. This method is used by |
| * {@link #inverseCumulativeProbability(double)} to find critical values. |
| * |
| * @param p the desired probability for the critical value |
| * @return domain value upper bound, i.e. |
| * P(X < <i>upper bound</i>) > <code>p</code> |
| */ |
| protected double getDomainUpperBound(double p) { |
| double ret; |
| |
| if (p < .5) { |
| ret = getMean(); |
| } else { |
| ret = Double.MAX_VALUE; |
| } |
| |
| return ret; |
| } |
| |
| /** |
| * Access the initial domain value, based on <code>p</code>, used to |
| * bracket a CDF root. This method is used by |
| * {@link #inverseCumulativeProbability(double)} to find critical values. |
| * |
| * @param p the desired probability for the critical value |
| * @return initial domain value |
| */ |
| protected double getInitialDomain(double p) { |
| double ret; |
| |
| if (p < .5) { |
| ret = getMean() - getStandardDeviation(); |
| } else if (p > .5) { |
| ret = getMean() + getStandardDeviation(); |
| } else { |
| ret = getMean(); |
| } |
| |
| return ret; |
| } |
| } |