Finite mixtures of censored Poisson regression models

While right‐censored data are very common in survival analysis, they may also occur in the case of count data. The literature contains models to treat such right‐censored count data. In this paper, we want to address issues of heterogeneity and clustering in this context. We propose a finite mixture of censored Poisson regressions to accommodate heterogeneity and also identify clusters in right‐censored count data. We also develop an expectation maximization algorithm to facilitate the estimation of such models and discuss the computational aspects of the proposed algorithm. We then present re... Mehr ...

Verfasser: Karlis, Dimitris
Dokumenttyp: Artikel
Reihe/Periodikum: Statistica Neerlandica
Verlag/Hrsg.: Oxford, Blackwell
Sprache: Englisch
ISSN: 0039-0402
Weitere Identifikatoren: doi: 10.1111/stan.12079
Permalink: https://search.fid-benelux.de/Record/olc-benelux-1974855511
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Datenquelle: Online Contents Benelux; Originalkatalog
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Link(s) : http://dx.doi.org/10.1111/stan.12079
http://dx.doi.org/10.1111/stan.12079