hgm-package {hgm} | R Documentation |
HGM
Description
The holonomic gradient method (HGM, hgm) gives a way to evaluate normalizing 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.
Details
Package: | hgm |
Type: | Package |
License: | GPL-2 |
LazyLoad: | yes |
The HGM and HGD are proposed in the paper below. This method based on the fact that a broad class of normalizing constants of unnormalized probability distributions belongs to the class of holonomic functions, which are solutions of holonomic systems of linear partial differential equations.
Note
This package includes a small subset of the Gnu scientific library codes (http://www.gnu.org/software/gsl/). Then, it might cause a conflict with the package gsl.
References
(N3OST2) Hiromasa Nakayama, Kenta Nishiyama, Masayuki Noro, Katsuyoshi Ohara, Tomonari Sei, Nobuki Takayama, Akimichi Takemura, Holonomic Gradient Descent and its Application to Fisher-Bingham Integral, Advances in Applied Mathematics 47 (2011), 639–658, doi: 10.1016/j.aam.2011.03.001
(dojo) Edited by T.Hibi, Groebner Bases: Statistics and Software Systems, Springer, 2013, doi: 10.1007/978-4-431-54574-3
See Also
hgm.ncBingham
,
hgm.ncorthant
,
hgm.ncso3
,
hgm.pwishart
,
hgm.Rhgm
hgm.p2wishart
,
Examples
## Not run:
example(hgm.ncBingham)
example(hgm.ncorthant)
example(hgm.ncso3)
example(hgm.pwishart)
example(hgm.Rhgm)
example(hgm.p2wishart)
## End(Not run)