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Parameter estimation for discretely observed linear birth-and-death processes

AC. Davison, S. Hautphenne, A. Kraus

. 2021 ; 77 (1) : 186-196. [pub] 20200508

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc22004562

Grantová podpora
GJ17-22950Y Grantová Agentura České Republiky
DE150101044 Australian Research Council

Birth-and-death processes are widely used to model the development of biological populations. Although they are relatively simple models, their parameters can be challenging to estimate, as the likelihood can become numerically unstable when data arise from the most common sampling schemes, such as annual population censuses. A further difficulty arises when the discrete observations are not equi-spaced, for example, when census data are unavailable for some years. We present two approaches to estimating the birth, death, and growth rates of a discretely observed linear birth-and-death process: via an embedded Galton-Watson process and by maximizing a saddlepoint approximation to the likelihood. We study asymptotic properties of the estimators, compare them on numerical examples, and apply the methodology to data on monitored populations.

Citace poskytuje Crossref.org

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