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%% $OpenXM: OpenXM/src/R/r-packages/hgm/man/hgm-package.Rd,v 1.9 2014/03/31 06:20:06 takayama Exp $ |
%% $OpenXM: OpenXM/src/R/r-packages/hgm/man/hgm-package.Rd,v 1.10 2014/03/31 07:23:09 takayama Exp $ |
\name{hgm-package} |
\name{hgm-package} |
\alias{hgm-package} |
\alias{hgm-package} |
\alias{HGM} |
\alias{HGM} |
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\description{ |
\description{ |
The holonomic gradient method (HGM, hgm) gives a way to evaluate normalizing |
The holonomic gradient method (HGM, hgm) gives a way to evaluate normalizing |
constants of unnormalized probability distributions by utilizing holonomic |
constants of unnormalized probability distributions by utilizing holonomic |
systems of differential equations. |
systems of differential or difference equations. |
The holonomic gradient descent (HGD, hgd) gives a method |
The holonomic gradient descent (HGD, hgd) gives a method |
to find maximal likelihood estimates by utilizing the HGM. |
to find maximal likelihood estimates by utilizing the HGM. |
} |
} |
Line 43 Tomonari Sei, Nobuki Takayama, Akimichi Takemura, |
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Line 43 Tomonari Sei, Nobuki Takayama, Akimichi Takemura, |
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Holonomic Gradient Descent and its Application to Fisher-Bingham Integral, |
Holonomic Gradient Descent and its Application to Fisher-Bingham Integral, |
Advances in Applied Mathematics 47 (2011), 639--658, |
Advances in Applied Mathematics 47 (2011), 639--658, |
\url{http://dx.doi.org/10.1016/j.aam.2011.03.001} |
\url{http://dx.doi.org/10.1016/j.aam.2011.03.001} |
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\item [dojo] Edited by T.Hibi, Groebner Bases: Statistics and Software Systems, Springer, 2013, |
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\url{http://dx.doi.org/10.1007/978-4-431-54574-3} |
\item \url{http://www.openxm.org} |
\item \url{http://www.openxm.org} |
} |
} |
} |
} |