Classical and Bayesian inference for the discrete Poisson Ramos-Louzada distribution with application to COVID-19 data

The present study is based on the derivation of a new extension of the Poisson distribution using the Ramos-Louzada distribution. Several statistical properties of the new distribution are derived including, factorial moments, moment-generating function, probability moments, skewness, kurtosis, and...

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Veröffentlicht in:Mathematical Biosciences and Engineering 2023-08, Vol.20 (8), p.14061-14080
1. Verfasser: Alkhairy, Ibrahim
Format: Artikel
Sprache:eng
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Zusammenfassung:The present study is based on the derivation of a new extension of the Poisson distribution using the Ramos-Louzada distribution. Several statistical properties of the new distribution are derived including, factorial moments, moment-generating function, probability moments, skewness, kurtosis, and dispersion index. Some reliability properties are also derived. The model parameter is estimated using different classical estimation techniques. A comprehensive simulation study was used to identify the best estimation method. Bayesian estimation with a gamma prior is also utilized to estimate the parameter. Three examples were used to demonstrate the utility of the proposed model. These applications revealed that the PRL-based model outperforms certain existing competing one-parameter discrete models such as the discrete Rayleigh, Poisson, discrete inverted Topp-Leone, discrete Pareto and discrete Burr-Hatke distributions.
ISSN:1551-0018
1551-0018
DOI:10.3934/mbe.2023628