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RCS file: /home/cvs/OpenXM/src/hgm/doc/ref-hgm.html,v
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retrieving revision 1.29
diff -u -p -r1.24 -r1.29
--- OpenXM/src/hgm/doc/ref-hgm.html 2018/03/19 01:17:46 1.24
+++ OpenXM/src/hgm/doc/ref-hgm.html 2019/10/31 01:53:51 1.29
@@ -2,6 +2,8 @@
+
+
References for HGM
@@ -12,11 +14,30 @@ the Holonomic Gradient Descent Method (HGD)
Papers and Tutorials
+-
+Anna-Laura Sattelberger, Bernd Sturmfels,
+D-Modules and Holonomic Functions
+ arxiv:1910.01395
+
-
+N.Takayama, L.Jiu, S.Kuriki, Y.Zhang,
+Computations of the Expected Euler Characteristic for the Largest Eigenvalue of a Real Wishart Matrix,
+ arxiv:1903.10099
+
- M.Harkonen, T.Sei, Y.Hirose,
+Holonomic extended least angle regression,
+ arxiv:1809.08190
+
- S.Mano,
+Partitions, Hypergeometric Systems, and Dirichlet Processes in Statistics,
+
+JSS Research Series in Statistics, 2018.
+
- A.Kume, T.Sei,
+On the exact maximum likelihood inference of Fisher–Bingham distributions using an adjusted holonomic gradient method,
+ doi (2018)
- Yoshihito Tachibana, Yoshiaki Goto, Tamio Koyama, Nobuki Takayama,
Holonomic Gradient Method for Two Way Contingency Tables,
- arxiv:1803.04170
-
- F.H.Danufane, K.Ohara, N.Takayama,
-Holonomic Gradient Method for the Distribution Function of the Largest Root of Complex Non-central Wishart Matrices,
+ arxiv:1803.04170
+
- 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),
arxiv:1707.02564
- T.Koyama,
An integral formula for the powered sum of the independent, identically and normally distributed random variables,
@@ -250,6 +271,6 @@ maximal Likehood estimates for the Fisher-Bingham dist
- d-dimensional Fisher-Bingham System
- $OpenXM: OpenXM/src/hgm/doc/ref-hgm.html,v 1.23 2017/07/12 01:32:58 takayama Exp $
+ $OpenXM: OpenXM/src/hgm/doc/ref-hgm.html,v 1.28 2019/04/23 22:51:12 takayama Exp $