On an integer-valued stochastic intensity model for time series of counts

Abdelhakim Aknouche and Stefanos Dimitrakopoulos

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a broad class of count time series models, the mixed Poisson integer-valued stochastic intensity models. The proposed specification encompasses a wide range of conditional distributions of counts. We study its probabilistic structure and design Markov chain Monte Carlo algorithms for two cases; the Poisson and the negative binomial distributions. The methodology is applied to simulated data as well as to various data sets. Model comparison using marginal likelihoods and forecast evaluation using point and density forecasts are also considered.

Keywords: Markov chain Monte Carlo; mixed Poisson process; parameter-driven models; count time series models. (search for similar items in EconPapers)
JEL-codes: C11 C13 C15 C18 C25 C5 C51 C53 C63 (search for similar items in EconPapers)
Date: 2020-01-01
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:105406

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