The linear birthdeath process: An inferential retrospective
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Authors
Tavaré, S
Publication Date
2018Journal Title
Advances in Applied Probability
ISSN
0001-8678
Publisher
Cambridge University Press (CUP)
Volume
50
Issue
A
Pages
253-269
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Tavaré, S. (2018). The linear birthdeath process: An inferential retrospective. Advances in Applied Probability, 50 (A), 253-269. https://doi.org/10.1017/apr.2018.84
Abstract
<jats:title>Abstract</jats:title><jats:p>
In this paper we provide an introduction to statistical inference for the classical linear birth‒death process, focusing on computational aspects of the problem in the setting of discretely observed processes. The basic probabilistic properties are given in Section 2, focusing on computation of the transition functions. This is followed by a brief discussion of simulation methods in Section 3, and of frequentist methods in Section 4. Section 5 is devoted to Bayesian methods, from rejection sampling to Markov chain Monte Carlo and approximate Bayesian computation. In Section 6 we consider the time-inhomogeneous case. The paper ends with a brief discussion in Section 7.
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Keywords
Approximate Bayesian computation, Markov chain Monte Carlo, estimation
Identifiers
External DOI: https://doi.org/10.1017/apr.2018.84
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287981
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