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Line 12  the Holonomic Gradient Descent Method  (HGD) </h1>
Line 14  the Holonomic Gradient Descent Method  (HGD) </h1>
   
 <h2> Papers  and Tutorials</h2>  <h2> Papers  and Tutorials</h2>
 <ol>  <ol>
   <li>
   N.Takayama, L.Jiu, S.Kuriki, Y.Zhang,
   Computations of the Expected Euler Characteristic for the Largest Eigenvalue of a Real Wishart Matrix,
   <a href="https://arxiv.org/abs/1903.10099"> arxiv:1903.10099 </a>
   <li> M.Harkonen, T.Sei, Y.Hirose,
   Holonomic extended least angle regression,
   <a href="https://arxiv.org/abs/1809.08190"> arxiv:1809.08190 </a>
   <li> S.Mano,
   Partitions, Hypergeometric Systems, and Dirichlet Processes in Statistics,
   <a href="https://www.springer.com/jp/book/9784431558866">
   JSS Research Series in Statistics</a>, 2018.
   <li> A.Kume, T.Sei,
   On the exact maximum likelihood inference of Fisher–Bingham distributions using an adjusted holonomic gradient method,
   <a href="https://doi.org/10.1007/s11222-017-9765-3"> doi </a> (2018)
   <li> Yoshihito Tachibana, Yoshiaki Goto, Tamio Koyama, Nobuki Takayama,
   Holonomic Gradient Method for Two Way Contingency Tables,
   <a href="https://arxiv.org/abs/1803.04170"> arxiv:1803.04170 </a>
   <li> F.H.Danufane, K.Ohara, N.Takayama, C.Siriteanu,
   Holonomic Gradient Method-Based CDF Evaluation for the Largest Eigenvalue of a Complex Noncentral Wishart Matrix
   (Title of the version 1: Holonomic Gradient Method for the Distribution Function of the Largest Root of Complex Non-central Wishart Matrices),
   <a href="https://arxiv.org/abs/1707.02564"> arxiv:1707.02564 </a>
   <li> T.Koyama,
   An integral formula for the powered sum of the independent, identically and normally distributed random variables,
   <a href="https://arxiv.org/abs/1706.03989"> arxiv:1706.03989 </a>
 <li> H.Hashiguchi, N.Takayama, A.Takemura,  <li> H.Hashiguchi, N.Takayama, A.Takemura,
 Distribution of Ratio of two Wishart Matrices and Evaluation of Cumulative Probability  Distribution of Ratio of two Wishart Matrices and Evaluation of Cumulative Probability
 by Holonomic Gradient Method,  by Holonomic Gradient Method,
Line 241  maximal Likehood estimates for the Fisher-Bingham dist
Line 267  maximal Likehood estimates for the Fisher-Bingham dist
 <li> <a href="http://www.math.kobe-u.ac.jp/OpenXM/Math/Fisher-Bingham-2"> d-dimensional Fisher-Bingham System </a>  <li> <a href="http://www.math.kobe-u.ac.jp/OpenXM/Math/Fisher-Bingham-2"> d-dimensional Fisher-Bingham System </a>
 </ol>  </ol>
   
 <pre> $OpenXM: OpenXM/src/hgm/doc/ref-hgm.html,v 1.21 2016/11/03 23:05:22 takayama Exp $ </pre>  <pre> $OpenXM: OpenXM/src/hgm/doc/ref-hgm.html,v 1.27 2018/11/13 01:14:49 takayama Exp $ </pre>
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