InverseGamma - LostTech.TensorFlow Documentation

Type InverseGamma

Namespace tensorflow.contrib.distributions

InverseGamma distribution.

The `InverseGamma` distribution is defined over positive real numbers using parameters `concentration` (aka "alpha") and `rate` (aka "beta").

#### Mathematical Details

The probability density function (pdf) is,

```none pdf(x; alpha, beta, x > 0) = x**(-alpha - 1) exp(-beta / x) / Z Z = Gamma(alpha) beta**-alpha ```

where:

* `concentration = alpha`, * `rate = beta`, * `Z` is the normalizing constant, and, * `Gamma` is the [gamma function]( https://en.wikipedia.org/wiki/Gamma_function).

The cumulative density function (cdf) is,

```none cdf(x; alpha, beta, x > 0) = GammaInc(alpha, beta / x) / Gamma(alpha) ```

where `GammaInc` is the [upper incomplete Gamma function]( https://en.wikipedia.org/wiki/Incomplete_gamma_function).

The parameters can be intuited via their relationship to mean and stddev,

```none concentration = alpha = (mean / stddev)**2 rate = beta = mean / stddev**2 ```

Distribution parameters are automatically broadcast in all functions; see examples for details.

WARNING: This distribution may draw 0-valued samples for small concentration values. See note in tf.random.gamma docstring.

#### Examples

Show Example

import tensorflow_probability as tfp
            tfd = tfp.distributions  dist = tfd.InverseGamma(concentration=3.0, rate=2.0)
dist2 = tfd.InverseGamma(concentration=[3.0, 4.0], rate=[2.0, 3.0])

Properties

Public properties

object allow_nan_stats get;

object allow_nan_stats_dyn get;

TensorShape batch_shape get;

object batch_shape_dyn get;

object concentration get;

Concentration parameter.

object concentration_dyn get;

Concentration parameter.

object dtype get;

object dtype_dyn get;

TensorShape event_shape get;

object event_shape_dyn get;

string name get;

object name_dyn get;

IDictionary<object, object> parameters get;

object parameters_dyn get;

object PythonObject get;

object rate get;

Rate parameter.

object rate_dyn get;