# LostTech.TensorFlow : API Documentation

Type InverseGamma

Namespace tensorflow.contrib.distributions

Parent Distribution

Interfaces IInverseGamma

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]) 

### Public properties

#### objectconcentration get;

Concentration parameter.

#### objectconcentration_dyn get;

Concentration parameter.

Rate parameter.

Rate parameter.