Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data
Statistics Theory
2011-12-19 v1 Statistics Theory
Abstract
We present symmetry tests for bifurcating autoregressive processes (BAR) when some data are missing. BAR processes typically model cell division data. Each cell can be of one of two types \emph{odd} or \emph{even}. The goal of this paper is to study the possible asymmetry between odd and even cells in a single observed lineage. We first derive asymmetry tests for the lineage itself, modeled by a two-type Galton-Watson process, and then derive tests for the observed BAR process. We present applications on both simulated and real data.
Keywords
Cite
@article{arxiv.1112.3745,
title = {Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data},
author = {Benoîte de Saporta and Anne Gégout-Petit and Laurence Marsalle},
journal= {arXiv preprint arXiv:1112.3745},
year = {2011}
}