Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Population based change-point detection for the identification of
  homozygosity islands   In this paper, we propose a new method for offline change-point detection on
some parameters of the distribution of a random vector. We introduce a
penalized maximum likelihood approach that can be efficiently computed by a
dynamic programming algorithm or approximated by a fast greedy binary splitting
algorithm. We prove both algorithms converge almost surely to the set of
change-points under very general assumptions on the distribution and
independent sampling of the random vector. In particular, we show the
assumptions leading to the consistency of the algorithms are satisfied by
categorical and Gaussian random variables. This new approach is motivated by
the problem of identifying homozygosity islands on the genome of individuals in
a population. Our method directly tackles the issue of identification of the
homozygosity islands at the population level, without the need of analyzing
single individuals and then combining the results, as is made nowadays in
state-of-the-art approaches.

27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin