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|a 10.1080/02664763.2020.1846692
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|a eng
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| 100 |
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|a Scollnik, David P M
|e verfasserin
|4 aut
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|a Bayesian analyses of an exponential-Poisson and related zero augmented type models
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|c 2022
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 16.06.2022
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|a published: Electronic-eCollection
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|a Citation Status PubMed-not-MEDLINE
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|a © 2020 Informa UK Limited, trading as Taylor & Francis Group.
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|a We consider several alternatives to the continuous exponential-Poisson distribution in order to accommodate the occurrence of zeros. Three of these are modifications of the exponential-Poisson model. One of these remains a fully continuous model. The other models we consider are all semi-continuous models, each with a discrete point mass at zero and a continuous density on the positive values. All of the models are applied to two environmental data sets concerning precipitation, and their Bayesian analyses using MCMC are discussed. This discussion covers convergence of the MCMC simulations and model selection procedures and considerations
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|a Journal Article
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|a 62p12
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|a Bayesian
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|a Markov chain Monte Carlo
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|a exponential-Poisson
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|a hurdle
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|a zero-inflated
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|i Enthalten in
|t Journal of applied statistics
|d 1991
|g 49(2022), 4 vom: 17., Seite 949-967
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|x 0266-4763
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|g year:2022
|g number:4
|g day:17
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