mxfusion.components.distributions.beta

Members

class mxfusion.components.distributions.beta.Beta(alpha, beta, rand_gen=None, dtype=None, ctx=None)

Bases: mxfusion.components.distributions.univariate.UnivariateDistribution

The one-dimensional beta distribution. The beta distribution can be defined over a scalar random variable or an array of random variables. In case of an array of random variables, a and b are broadcasted to the shape of the output random variable (array).

Parameters:
  • alpha (Variable) – a parameter (alpha) of the beta distribution.
  • beta (Variable) – b parameter (beta) of the beta distribution.
  • rand_gen (RandomGenerator) – the random generator (default: MXNetRandomGenerator).
  • dtype (numpy.float32 or numpy.float64) – the data type for float point numbers.
  • ctx (None or mxnet.cpu or mxnet.gpu) – the mxnet context (default: None/current context).
log_pdf_impl(alpha, beta, random_variable, F=None)

Computes the logarithm of the probability density function (PDF) of the beta distribution.

Parameters:
  • alpha (MXNet NDArray or MXNet Symbol) – the a parameter (alpha) of the beta distribution.
  • beta (MXNet NDArray or MXNet Symbol) – the b parameter (beta) of the beta distributions.
  • random_variable (MXNet NDArray or MXNet Symbol) – the random variable of the beta distribution.
  • F – the MXNet computation mode (mxnet.symbol or mxnet.ndarray).
Returns:

log pdf of the distribution.
Rtypes:

MXNet NDArray or MXNet Symbol
draw_samples_impl(alpha, beta, rv_shape, num_samples=1, F=None)

Draw samples from the beta distribution.

If X and Y are independent, with $X sim Gamma(lpha, heta)$ and $Y sim Gamma(eta, heta)$ then $

rac {X}{X+Y}}sim mathrm {B} (lpha ,eta ).}$

param alpha:the a parameter (alpha) of the beta distribution.
type alpha:MXNet NDArray or MXNet Symbol
param beta:the b parameter (beta) of the beta distributions.
type beta:MXNet NDArray or MXNet Symbol
param rv_shape:the shape of each sample.
type rv_shape:tuple
param num_samples:
 the number of drawn samples (default: one).
type num_samples:
 int
param F:the MXNet computation mode (mxnet.symbol or mxnet.ndarray).
returns:a set samples of the beta distribution.
rtypes:MXNet NDArray or MXNet Symbol
static define_variable(alpha=1.0, beta=1.0, shape=None, rand_gen=None, dtype=None, ctx=None)

Creates and returns a random variable drawn from a beta distribution.

Parameters:
  • a – The a parameter (alpha) of the distribution.
  • b – The b parameter (beta) of the distribution.
  • shape (tuple or [tuple]) – the shape of the random variable(s).
  • rand_gen (RandomGenerator) – the random generator (default: MXNetRandomGenerator).
  • dtype (numpy.float32 or numpy.float64) – the data type for float point numbers.
  • ctx (None or mxnet.cpu or mxnet.gpu) – the mxnet context (default: None/current context).
Returns:

the random variables drawn from the beta distribution.
Rtypes:

Variable