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Statistical estimation of a growth-fragmentation model observed on a genealogical tree

Abstract : We raise the issue of estimating the division rate for a growing and dividing population modelled by a piecewise deterministic Markov branching tree. Such models have broad applications, ranging from TCP/IP window size protocol to bacterial growth. Here, the individ-uals split into two offsprings at a division rate B(x) that depends on their size x, whereas their size grow exponentially in time, at a rate that exhibits variability. The mean empirical measure of the model satisfies a growth-fragmentation type equation, and we bridge the determinis-tic and probabilistic viewpoints. We then construct a nonparametric estimator of the division rate B(x) based on the observation of the pop-ulation over different sampling schemes of size n on the genealogical tree. Our estimator nearly achieves the rate n −s/(2s+1) in squared-loss error asymptotically, generalizing and improving on the rate n −s/(2s+3) obtained in [13, 15] through indirect observation schemes. Our method is consistently tested numerically and implemented on Escherichia coli data, which demonstrates its major interest for practical applications.
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Contributor : Marc Hoffmann Connect in order to contact the contributor
Submitted on : Tuesday, January 13, 2015 - 3:15:15 PM
Last modification on : Wednesday, January 26, 2022 - 5:42:04 PM
Long-term archiving on: : Saturday, September 12, 2015 - 1:55:30 AM


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Marie Doumic, Marc Hoffmann, Nathalie Krell, Lydia Robert. Statistical estimation of a growth-fragmentation model observed on a genealogical tree. Bernoulli, Bernoulli Society for Mathematical Statistics and Probability, 2015, 21 (3), pp.1760-1799. ⟨10.3150/14-BEJ623⟩. ⟨hal-01102799⟩



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