The linear birthdeath process: An inferential retrospective


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)