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: |
1.20 |
| Depends: |
R (≥ 2.6.0), deSolve |
| Published: |
2022-04-07 |
| 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 |
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