Package: hgm 1.23

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.

Authors:Nobuki Takayama, Tamio Koyama, Tomonari Sei, Hiromasa Nakayama, Kenta Nishiyama

hgm_1.23.tar.gz
hgm_1.23.zip(r-4.7)hgm_1.23.zip(r-4.6)hgm_1.23.zip(r-4.5)
hgm_1.23.tgz(r-4.6-x86_64)hgm_1.23.tgz(r-4.6-arm64)hgm_1.23.tgz(r-4.5-x86_64)hgm_1.23.tgz(r-4.5-arm64)
hgm_1.23.tar.gz(r-4.7-arm64)hgm_1.23.tar.gz(r-4.7-x86_64)hgm_1.23.tar.gz(r-4.6-arm64)hgm_1.23.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
hgm/json (API)

# Install 'hgm' in R:
install.packages('hgm', repos = c('https://nobuki-takayama.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

1.00 score 1 stars 9 scripts 141 downloads 7 exports 1 dependencies

Last updated from:c88285545b. Checks:11 NOTE, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE116
linux-devel-x86_64NOTE101
source / vignettesOK145
linux-release-arm64NOTE119
linux-release-x86_64NOTE104
macos-release-arm64NOTE135
macos-release-x86_64NOTE397
macos-oldrel-arm64NOTE275
macos-oldrel-x86_64NOTE331
windows-develNOTE82
windows-releaseNOTE89
windows-oldrelNOTE106
wasm-releaseFAIL91

Exports:hgm.ncBinghamhgm.ncorthanthgm.ncso3hgm.p2wisharthgm.pwisharthgm.Rhgmhgm.Rhgm.demo1

Dependencies:deSolve