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hgm (version 1.11)

Holonomic Gradient Method and Gradient Descent

Description

The holonomic gradient method (HGM, hgm) gives a way to evaluate normalization constants of unnormalized probability distributions by utilizing holonomic systems of differential or difference equations. The holonomic gradient descent (HGD, hgd) gives a method to find maximal likelihood estimates by utilizing the HGM.

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Version

Install

install.packages('hgm')

Monthly Downloads

192

Version

1.11

License

GPL-2

Maintainer

Nobuki Takayama

Last Published

April 3rd, 2015

Functions in hgm (1.11)

hgm-package

HGM
hgm.ncorthant

The function hgm.ncorthant evaluates the orthant probability.
hgm.ncBingham

The function hgm.ncBingham performs the holonomic gradient method (HGM) for Bingham distributions.
hgm.Rhgm.demo1

The function hgm.Rhgm.demo1 performs a demonstration of the function hgm.Rhgm.
hgm.ncso3

The function hgm.ncso3 evaluates the normalization constant for the Fisher distribution on SO(3).
hgm.Rhgm

The function hgm.Rhgm performs the holonomic gradient method (HGM) for a given Pfaffian system and an initial value vector.
hgm.pwishart

The function hgm.pwishart evaluates the cumulative distribution function of random wishart matrices.