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The linear birthdeath process: An inferential retrospective

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Tavaré, S 

Abstract

jats:titleAbstract</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. </jats:p>

Description

Keywords

Approximate Bayesian computation, Markov chain Monte Carlo, estimation

Journal Title

Advances in Applied Probability

Conference Name

Journal ISSN

0001-8678
1475-6064

Volume Title

50

Publisher

Cambridge University Press (CUP)