On parameter estimation in population models.

J V Ross; T Taimre; P K Pollett

doi:10.1016/j.tpb.2006.08.001

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PubMed · 16984803

On parameter estimation in population models.

J V Ross·T Taimre·P K Pollett

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Abstract

We describe methods for estimating the parameters of Markovian population processes in continuous time, thus increasing their utility in modelling real biological systems. A general approach, applicable to any finite-state continuous-time Markovian model, is presented, and this is specialised to a computationally more efficient method applicable to a class of models called density-dependent Markov population processes. We illustrate the versatility of both approaches by estimating the parameters of the stochastic SIS logistic model from simulated data. This model is also fitted to data from a population of Bay checkerspot butterfly (Euphydryas editha bayensis), allowing us to assess the viability of this population.

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Animals Butterflies Markov Chains Models, Theoretical Stochastic Processes Journal Article Research Support, Non-U.S. Gov't

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J V Ross, T Taimre, P K Pollett. 2006-08-12. On parameter estimation in population models.. https://doi.org/10.1016/j.tpb.2006.08.001

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