rInvGamma

integer, number of samples to be generated.

numeric, the shape parameter of gamma distribution.

shape

numeric, the scale, or inverse-scale parameter of gamma distribution. The 'rate' parameter in Gamma is the 'scale' parameter in InvGamma.

scale

Generation random samples from Inverse-Gamma distribution. For a random variable x, the density function is defined as:
 $$(rate^shape)/Gamma(shape) x^{-shape-1} exp(-rate/x)$$
Where Gamma() is the Gamma function.

A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include linear Gaussian systems, Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, sampling from posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.

rInvGamma: Random number generation of Inverse-Gamma distribution

Description

Usage

Arguments

Value