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On Classes of Equivalence and Identifiability of Age-Dependent Branching Processes

Published online by Cambridge University Press:  22 February 2016

Rui Chen*
Affiliation:
University of Rochester
Ollivier Hyrien*
Affiliation:
University of Rochester
*
Postal address: Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA.
Postal address: Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14642, USA.
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Abstract

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Age-dependent branching processes are increasingly used in analyses of biological data. Despite being central to most statistical procedures, the identifiability of these models has not been studied. In this paper we partition a family of age-dependent branching processes into equivalence classes over which the distribution of the population size remains identical. This result can be used to study identifiability of the offspring and lifespan distributions for parametric families of branching processes. For example, we identify classes of Markov processes that are not identifiable. We show that age-dependent processes with (nonexponential) gamma-distributed lifespans are identifiable and that Smith-Martin processes are not always identifiable.

Type
General Applied Probability
Copyright
© Applied Probability Trust 

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