mxnet.gluon.probability.distributions.gamma¶

Gamma Distribution.

Classes

Gamma(shape[, scale, validate_args])

Create a Gamma distribution object.

class mxnet.gluon.probability.distributions.gamma.Gamma(shape, scale=1.0, validate_args=None)[source]¶

Create a Gamma distribution object.

Parameters:

shape (Tensor or scalar) – shape parameter of the distribution, often represented by k or alpha
scale (Tensor or scalar, default 1) – scale parameter of the distribution, often represented by theta, theta = 1 / beta, where beta stands for the rate parameter.

broadcast_to(batch_shape)[source]¶

Returns a new distribution instance with parameters expanded to batch_shape. This method calls numpy.broadcast_to on the parameters.

Parameters:: batch_shape (Tuple) – The batch shape of the desired distribution.

entropy()[source]¶: Return the entropy of a distribution. The entropy of distributions in exponential families could be computed by: H(P) = F(theta) - <theta, F(theta)’> - E_p[k(x)]

log_prob(value)[source]¶: Returns the log of the probability density/mass function evaluated at value.

sample_n(size=None)[source]¶: Generate samples of (n + parameter_shape) from the distribution.