RIEMANNIAN STRUCTURE FOR CORRELATION MATRICES

被引:6
|
作者
David, Paul [1 ]
Gu, Weiqing [2 ]
机构
[1] Claremont Grad Univ, Claremont, CA 91711 USA
[2] Harvey Mudd Coll, Claremont, CA 91711 USA
来源
OPERATORS AND MATRICES | 2019年 / 13卷 / 03期
关键词
Riemannian geometry; correlation; Newton's method; quotient manifold; optimization; DISTRIBUTIONS; MANIFOLDS; GEOMETRY; SPACE;
D O I
10.7153/oam-2019-13-46
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this paper we present a new approach to viewing the set of non-degenerate correlation matrices Corr(n) as a manifold and provide an optimization procedure using its new found Riemannian structure. First we give a proof that Corr(n) is a quotient submanifold of the symmetric positive-definite matrices SPD(n) obtained via a Lie group action of positive diagonal matrices Diag(+)(n). With this structure Corr(n) naturally inherits a Riemannian metric from SPD(n) and therefore enables us to develop a Riemannian-based Newton's method on Corr(n). We subsequently compare this Newton method to other optimization methods on Corr(n).
引用
收藏
页码:607 / 627
页数:21
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