Journal article

Fitting Markovian binary trees using global and individual demographic data

Sophie Hautphenne, Melanie Massaro, Katharine Turner

Theoretical Population Biology | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2019


We consider a class of continuous-time branching processes called Markovian binary trees (MBTs), in which the individuals lifetime and reproduction epochs are modelled using a transient Markovian arrival process (TMAP). We develop methods for estimating the parameters of the TMAP by using either age-specific averages of reproduction and mortality rates, or age-specific individual demographic data. Depending on the degree of detail of the available information, we follow a weighted non-linear regression or a maximum likelihood approach. We discuss several criteria to determine the optimal number of states in the underlying TMAP. Our results improve the fit of an existing MBT model for human d..

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Awarded by Australian Research Council (ARC)

Awarded by New Zealand Foundation for Research, Science and Technology

Funding Acknowledgements

We thank the referee and associate editor for constructive comments which helped us to improve the paper. Sophie Hautphenne thanks the Australian Research Council (ARC) for support through the Discovery Early Career Researcher Award DE150101044. The black robin research was funded by the New Zealand Foundation for Research, Science and Technology (UOCX0601) to Melanie Massaro, by the School of Biological Sciences, University of Canterbury, by the Brian Mason Scientific and Technical Trust, New Zealand, and by the Mohamed bin Zayed Species Conservation Fund. This research was only possible with permission from the Chatham Island Conservation Board and the logistic help of the Department of Conservation, New Zealand.