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A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

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Abstract

In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The estimation and inferences of the model parameters were made considering a Bayesian approach using the algorithm of Hamiltonian Markov chain Monte Carlo methods to simulate samples of the joint posterior distribution of interest. Two applications were made for the analysis of paired count data.

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Acknowledgements

We are indebted to the Editorial Boarding and Referees for their valuable comments, criticisms and suggestions which have substantially improved the text of the manuscript. This work was partially funded by the Brazilian institution FAPESP, Grants 2019/21766-8 Marinho G. Andrade and Grants 2019/22412-5 Katiane S. Conceição.

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  1. Departamento de Matemática Aplicada e Estatística, ICMC, Universidade de São Paulo, São Carlos, SP, Brazil

    Katiane S. Conceição, Adriano K. Suzuki & Marinho G. Andrade

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  1. Katiane S. Conceição
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  2. Adriano K. Suzuki
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  3. Marinho G. Andrade
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Correspondence to Marinho G. Andrade.

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Conceição, K.S., Suzuki, A.K. & Andrade, M.G. A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC. Stat Methods Appl 30, 747–765 (2021). https://doi.org/10.1007/s10260-020-00541-7

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  • DOI: https://doi.org/10.1007/s10260-020-00541-7

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