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Bayesian analysis of time series Poisson data

Title
Bayesian analysis of time series Poisson data
Authors
Oh, MSLim, YB
Ewha Authors
임용빈
SCOPUS Author ID
임용빈scopus
Issue Date
2001
Journal Title
JOURNAL OF APPLIED STATISTICS
ISSN
0266-4763JCR Link
Citation
vol. 28, no. 2, pp. 259 - 271
Publisher
CARFAX PUBLISHING
Indexed
SCIE; SCOPUS WOS
Abstract
This paper provides a practical simulation-based Bayesian analysis of parameter-driven models for time series Poisson data with the AR(1) latent process. The posterior distribution is simulated by a Gibbs sampling algorithm. Full conditional posterior distributions of unknown variables in the model are given in convenient forms for the Gibbs sampling algorithm. The case with missing observations is also discussed. The methods are applied to real polio data from 1970 to 1983.
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자연과학대학 > 통계학전공 > Journal papers
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