Asymmetry tests for bifurcating auto-regressive processes with missing data
Copyright policy )Asymmetry tests for bifurcating auto-regressive processes with missing data
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.
Non-Markovian processes: hypothesis testing, [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], Asymptotic properties of parametric tests, Censored data models, Mathematics - Statistics Theory, Statistics Theory (math.ST), cell division data, Applications of statistics to biology and medical sciences; meta analysis, missing data, Time series, auto-correlation, regression, etc. in statistics (GARCH), two-type Galton-Watson model, Branching processes (Galton-Watson, birth-and-death, etc.), FOS: Mathematics, bifurcating autoregressive processes, Wald's test
Non-Markovian processes: hypothesis testing, [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], Asymptotic properties of parametric tests, Censored data models, Mathematics - Statistics Theory, Statistics Theory (math.ST), cell division data, Applications of statistics to biology and medical sciences; meta analysis, missing data, Time series, auto-correlation, regression, etc. in statistics (GARCH), two-type Galton-Watson model, Branching processes (Galton-Watson, birth-and-death, etc.), FOS: Mathematics, bifurcating autoregressive processes, Wald's test
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