Quotation Frühwirth-Schnatter, Sylvia, Wagner, Helga. 2006. Auxiliary mixture sampling for parameter-driven models of time series of small counts with applications to state space modelling. Biometrika 93 (4): 827-841.


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Abstract

We consider parameter-driven models of time series of counts, where the observations are assumed to arise from a Poisson distribution with a mean changing over time according to a latent process. Estimation of these models is carried out within a Bayesian framework using data augmentation and Markov chain Monte Carlo methods. We suggest a new auxiliary mixture sampler, which possesses a Gibbsian transition kernel, where we draw from full conditional distributions belonging to standard distribution families only. Emphasis lies on application to state space modelling of time series of counts, but we show that auxiliary mixture sampling may be applied to a wider range of parameter-driven models, including random-effects models and panel data models based on the Poisson distribution.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Biometrika
Citation Index SCI
WU Journalrating 2009 A
WU-Journal-Rating new FIN-A, VW-B, WH-A
Language English
Title Auxiliary mixture sampling for parameter-driven models of time series of small counts with applications to state space modelling
Volume 93
Number 4
Year 2006
Page from 827
Page to 841
URL http://biomet.oxfordjournals.org/content/93/4/827.abstract

Associations

People
Frühwirth-Schnatter, Sylvia (Details)
External
Wagner, Helga
Organization
Institute for Statistics and Mathematics IN (Details)
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