@inbook{ba3532515bea4a79abb0cc1afc7c9221,
title = "Stochastic Population Models",
abstract = "In this chapter, we introduce stochastic population processes, and more specifically Markov population processes. We give basic definitions and examples from the scientific literature to illustrate the process of building these stochastic models. We then discuss approximations to these stochastic processes when the population is large and review numerical schemes for stochastic simulation that rely on these approximations. We then review and suggest practical statistical inference methods for observations that arise from these stochastic population models, including when these models are generalized to a spatio-temporal framework.",
keywords = "Diffusion approximation, Markov processes, Spatio-temporal statistics, Statistical inference for stochastic processes, Stochastic population models, Stochastic simulation",
author = "John Fricks and Ephraim Hanks",
year = "2018",
month = jan,
day = "1",
doi = "10.1016/bs.host.2018.07.012",
language = "English (US)",
isbn = "9780444640727",
series = "Handbook of Statistics",
publisher = "Elsevier B.V.",
pages = "443--480",
editor = "{Srinivasa Rao}, {Arni S.R.} and C.R. Rao",
booktitle = "Handbook of Statistics",
}