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``mx.nd.random.pdf.negative.binomial``
============================================================================
Description
----------------------
Computes the value of the PDF of samples of
negative binomial distributions with parameters *k* (failure limit) and *p* (failure probability).
*k* and *p* must have the same shape, which must match the leftmost subshape
of *sample*. That is, *sample* can have the same shape as *k* and *p*, in which
case the output contains one density per distribution, or *sample* can be a tensor
of tensors with that shape, in which case the output is a tensor of densities such that
the densities at index *i* in the output are given by the samples at index *i* in *sample*
parameterized by the values of *k* and *p* at index *i*.
**Example**::
random_pdf_negative_binomial(sample=[[1,2,3,4]], k=[1], p=a[0.5]) =
[[0.25, 0.125, 0.0625, 0.03125]]
# Note that k may be real-valued
sample = [[1,2,3,4],
[1,2,3,4]]
random_pdf_negative_binomial(sample=sample, k=[1, 1.5], p=[0.5, 0.5]) =
[[0.25, 0.125, 0.0625, 0.03125 ],
[0.26516506, 0.16572815, 0.09667476, 0.05437956]]
Arguments
------------------
+----------------------------------------+------------------------------------------------------------+
| Argument | Description |
+========================================+============================================================+
| ``sample`` | NDArray-or-Symbol. |
| | |
| | Samples from the distributions. |
+----------------------------------------+------------------------------------------------------------+
| ``k`` | NDArray-or-Symbol. |
| | |
| | Limits of unsuccessful experiments. |
+----------------------------------------+------------------------------------------------------------+
| ``is.log`` | boolean, optional, default=0. |
| | |
| | If set, compute the density of the log-probability instead |
| | of the |
| | probability. |
+----------------------------------------+------------------------------------------------------------+
| ``p`` | NDArray-or-Symbol. |
| | |
| | Failure probabilities in each experiment. |
+----------------------------------------+------------------------------------------------------------+
Value
----------
``out`` The result mx.ndarray
Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/random/pdf_op.cc#L310