LostTech.TensorFlow : API Documentation

Type Kumaraswamy

Namespace tensorflow.contrib.distributions.bijectors

Parent Bijector

Interfaces IKumaraswamy

Compute `Y = g(X) = (1 - (1 - X)**(1 / b))**(1 / a), X in [0, 1]`.

This bijector maps inputs from `[0, 1]` to [0, 1]`. The inverse of the bijector applied to a uniform random variable `X ~ U(0, 1) gives back a random variable with the [Kumaraswamy distribution]( https://en.wikipedia.org/wiki/Kumaraswamy_distribution):

```none Y ~ Kumaraswamy(a, b) pdf(y; a, b, 0 <= y <= 1) = a * b * y ** (a - 1) * (1 - y**a) ** (b - 1) ```

Properties

Public properties

object concentration0 get;

The `b` in: `Y = g(X) = (1 - (1 - X)**(1 / b))**(1 / a)`.

object concentration0_dyn get;

The `b` in: `Y = g(X) = (1 - (1 - X)**(1 / b))**(1 / a)`.

object concentration1 get;

The `a` in: `Y = g(X) = (1 - (1 - X)**(1 / b))**(1 / a)`.

object concentration1_dyn get;

The `a` in: `Y = g(X) = (1 - (1 - X)**(1 / b))**(1 / a)`.

object dtype get;

object dtype_dyn get;

object forward_min_event_ndims get;

object forward_min_event_ndims_dyn get;

IList<object> graph_parents get;

object graph_parents_dyn get;

object inverse_min_event_ndims get;

object inverse_min_event_ndims_dyn get;

bool is_constant_jacobian get;

object is_constant_jacobian_dyn get;

object name get;

object name_dyn get;

object PythonObject get;

bool validate_args get;

object validate_args_dyn get;