Alkhairy I. Classical and Bayesian inference for the discrete Poisson Ramos-Louzada distribution with application to COVID-19 data.
MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023;
20:14061-14080. [PMID:
37679125 DOI:
10.3934/mbe.2023628]
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Abstract
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.
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