Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data
DE SAPORTA, Benoîte
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Groupe de Recherche en Economie Théorique et Appliquée [GREThA]
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Groupe de Recherche en Economie Théorique et Appliquée [GREThA]
GÉGOUT-PETIT, Anne
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
DE SAPORTA, Benoîte
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Groupe de Recherche en Economie Théorique et Appliquée [GREThA]
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Groupe de Recherche en Economie Théorique et Appliquée [GREThA]
GÉGOUT-PETIT, Anne
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
< Réduire
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Langue
en
Article de revue
Ce document a été publié dans
Statistics and Probability Letters. 2012, vol. 82, n° 7, p. 1439-1444
Elsevier
Résumé en anglais
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 ...Lire la suite >
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.< Réduire
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