Resumen

SADEGHKHANI, Abdolnasser  y  AHMED, S. Ejaz. On Predictive Distribution of K-Inflated Poisson Models with and Without Additional Information. Rev.Colomb.Estad. [online]. 2020, vol.43, n.2, pp.173-182.  Epub 05-Dic-2020. ISSN 0120-1751.  https://doi.org/10.15446/rce.v43n2.81979.

This paper addresses different approaches in finding the Bayesian predictive distribution of a random variable from a Poisson model that can handle count data with an inflated value of K Є ℕ, known as the KIP model. We explore how we can use other source of additional information to find such an estimator. More specifically, we find a Bayesian estimator of future density of random variable Y 1 , based on observable X 1 from the K1IP(p1 , λ 1 ) model, with and without assuming that there exists another random variable X 2 , from the K2IP(p 2 , λ 2 ) model, independent of X1, provided λ 1 ≥ λ 2, and compare their performance using simulation method.

Palabras clave : KIP model; Bayesian statistics; Bayesian predictive distribution; Simulation.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )