hgm: Holonomic Gradient Method and Gradient Descent

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.

Version: 1.18
Depends: R (≥ 2.6.0), deSolve
Published: 2020-02-06
Author: Nobuki Takayama, Tamio Koyama, Tomonari Sei, Hiromasa Nakayama, Kenta Nishiyama
Maintainer: Nobuki Takayama <takayama at math.kobe-u.ac.jp>
License: GPL-2
URL: http://www.openxm.org
NeedsCompilation: yes
CRAN checks: hgm results


Reference manual: hgm.pdf
Package source: hgm_1.18.tar.gz
Windows binaries: r-devel: hgm_1.18.zip, r-release: hgm_1.18.zip, r-oldrel: hgm_1.18.zip
macOS binaries: r-release: hgm_1.18.tgz, r-oldrel: hgm_1.18.tgz
Old sources: hgm archive


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