M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation

Details M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation

2008-02-12

arxiv.org/abs/0802.1669v2

Statistics

Methodology

30 pages, 13 figures

Scientific paper

Chia and Nakano (2009) introduced the concept of M-decomposability of probability densities in one-dimension. In this paper, we generalize M-decomposability to any dimension. We prove that all elliptical unimodal densities are M-undecomposable. We also derive an inequality to show that it is better to represent an M-decomposable density via a mixture of unimodal densities. Finally, we demonstrate the application of M-decomposability to clustering and kernel density estimation, using real and simulated data. Our results show that M-decomposability can be used as a non-parametric criterion to locate modes in probability densities.

Affiliated with

Also associated with

No associations

Rating

M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and M-decomposability, elliptical unimodal densities, and applications to clustering and kernel density estimation will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-108673