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hgm  

Holonomic Gradient Method and Gradient Descent
View on CRAN: Click here


Download and install hgm package within the R console
Install from CRAN:
install.packages("hgm")

Install from Github:
library("remotes")
install_github("cran/hgm")

Install by package version:
library("remotes")
install_version("hgm", "1.23")



Attach the package and use:
library("hgm")
Maintained by
Nobuki Takayama
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-03-27
Latest Update: 2023-01-31
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.
How to cite:
Nobuki Takayama (2015). hgm: Holonomic Gradient Method and Gradient Descent. R package version 1.23, https://cran.r-project.org/web/packages/hgm. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.10 (2015-03-27 07:16), 1.11 (2015-04-03 07:48), 1.16 (2016-10-30 11:41), 1.17 (2017-04-02 01:13), 1.18 (2020-02-06 13:10), 1.20 (2022-04-07 09:42), 1.22 (2022-10-26 12:45)
Other packages that cited hgm R package
View hgm citation profile
Other R packages that hgm depends, imports, suggests or enhances
Complete documentation for hgm
Functions, R codes and Examples using the hgm R package
Some associated functions: hgm-package . hgm.Rhgm.demo1 . hgm.Rhgm . hgm.c2wishart . hgm.cwishart . hgm.ncorthant . hgm.se.hgm.Bingham . hgm.so3nc . 
Some associated R codes: hgm.c2wishart.R . hgm.cwishart.R . hgm.so3nc.R . ko_orthant.R . se_bingham.R . se_demo.R . se_hgm.R . zhgm_names.R .  Full hgm package functions and examples
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