Literature DB >> 31823352

On continuous-time capture-recapture in closed populations.

Wei Zhang1, Simon J Bonner1,2.   

Abstract

Schofield et al. (2018, Biometrics 74, 626-635) presented simple and efficient algorithms for fitting continuous-time capture-recapture models based on Poisson processes. They also demonstrated by real examples that the standard method of discretizing continuous-time capture-recapture data and then fitting traditional discrete-time models may lead to information loss in population size estimation. In this article, we aim to clarify that key to the approach of Schofield et al. (2018) is the Poisson model assumed for the number of captures of each individual throughout the study, rather than the fact of data being collected in continuous time. We further show that the method of data discretization works equally well as the method of Schofield et al. (2018), provided that a Poisson model is applied instead of the traditional Bernoulli model to the number of captures for each individual on each sampling occasion.
© 2019 The International Biometric Society.

Keywords:  Poisson model; S-ancillarity; capture-recapture; continuous-time; data discretization; likelihood factorization

Year:  2019        PMID: 31823352     DOI: 10.1111/biom.13185

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  1 in total

1.  Population Size Estimation using Zero-truncated Poisson Regression with Measurement Error.

Authors:  Wen-Han Hwang; Jakub Stoklosa; Ching-Yun Wang
Journal:  J Agric Biol Environ Stat       Date:  2022-01-12       Impact factor: 2.267

  1 in total

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