mxnet.gluon.probability.distributions.exponential

Exponential Distribution.

Classes

Exponential([scale, validate_args])

Create a Exponential distribution object parameterized by scale.

class mxnet.gluon.probability.distributions.exponential.Exponential(scale=1.0, validate_args=None)

Bases: ExponentialFamily

Create a Exponential distribution object parameterized by scale.

Parameters:

scale (Tensor or scalar) – Scale of the distribution. (scale = 1 /rate)

broadcast_to(batch_shape)

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.

cdf(value)

Returns the cumulative density/mass function evaluated at value.

entropy()

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)]

icdf(value)

Returns the inverse cumulative density/mass function evaluated at value.

log_prob(value)

Returns the log of the probability density/mass function evaluated at value.

property mean

Returns the mean of the distribution.

sample(size=None)

Generates a shape shaped sample.

sample_n(size=None)

Generate samples of (n + parameter_shape) from the distribution.

property stddev

Returns the standard deviation of the distribution.

property variance

Returns the variance of the distribution.