Mixtures of concentrated multivariate sine distributions with applications to bioinformatics

TY - JOUR

T1 - Mixtures of concentrated multivariate sine distributions with applications to bioinformatics

AU - Mardia, Kanti V.

AU - Kent, John T.

AU - Zhang, Zhengzheng

AU - Taylor, Charles C.

AU - Hamelryck, Thomas

PY - 2012

Y1 - 2012

N2 - Motivated by examples in protein bioinformatics, we study a mixture model of multivariate angular distributions. The distribution treated here (multivariate sine distribution) is a multivariate extension of the well-known von Mises distribution on the circle. The density of the sine distribution has an intractable normalizing constant and here we propose to replace it in the concentrated case by a simple approximation. We study the EM algorithm for this distribution and apply it to a practical example from protein bioinformatics.

AB - Motivated by examples in protein bioinformatics, we study a mixture model of multivariate angular distributions. The distribution treated here (multivariate sine distribution) is a multivariate extension of the well-known von Mises distribution on the circle. The density of the sine distribution has an intractable normalizing constant and here we propose to replace it in the concentrated case by a simple approximation. We study the EM algorithm for this distribution and apply it to a practical example from protein bioinformatics.

U2 - 10.1080/02664763.2012.719221

DO - 10.1080/02664763.2012.719221

M3 - Journal article

SN - 0266-4763

VL - 39

SP - 2475

EP - 2492

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

IS - 11

ER -