Table Of Contents
Table Of Contents

mx.nd.sample.negative.binomial

Description

Concurrent sampling from multiple negative binomial distributions with parameters k (failure limit) and p (failure probability).

The parameters of the distributions are provided as input arrays. Let [s] be the shape of the input arrays, n be the dimension of [s], [t] be the shape specified as the parameter of the operator, and m be the dimension of [t]. Then the output will be a (n+m)-dimensional array with shape [s]x[t].

For any valid n-dimensional index i with respect to the input arrays, output[i] will be an m-dimensional array that holds randomly drawn samples from the distribution which is parameterized by the input values at index i. If the shape parameter of the operator is not set, then one sample will be drawn per distribution and the output array has the same shape as the input arrays.

Samples will always be returned as a floating point data type.

Example:

k = [ 20, 49 ]
p = [ 0.4 , 0.77 ]

// Draw a single sample for each distribution
sample_negative_binomial(k, p) = [ 15.,  16.]

// Draw a vector containing two samples for each distribution
sample_negative_binomial(k, p, shape=(2)) = [[ 15.,  50.],
[ 16.,  12.]]

Arguments

Argument

Description

k

NDArray-or-Symbol.

Limits of unsuccessful experiments.

shape

Shape(tuple), optional, default=[].

Shape to be sampled from each random distribution.

dtype

{‘None’, ‘float16’, ‘float32’, ‘float64’},optional, default=’None’.

DType of the output in case this can’t be inferred. Defaults to float32 if not defined (dtype=None).

p

NDArray-or-Symbol.

Failure probabilities in each experiment.