On a family that unifies Generalized Marshall-Olkin and Poisson-G family\n of distribution

2020/06/06 by Laba Handique, Handique, Laba, Farrukh Jamal +3
Computer Science · Decision Sciences · Environmental Science · Mathematics · #60E05 #62E15 #Bayesian Methods and Mixture Models #FOS: Mathematics #G.3 #Hydrology and Drought Analysis #Probabilistic and Robust Engineering Design #Statistical Distribution Estimation and Applications #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.2006.05816

openalex publication_date 2020/06/06 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

Unifying the generalized Marshall-Olkin (GMO) and Poisson-G (P-G) a new\nfamily of distribution is proposed. Density and the survival function are\nexpressed as infinite mixtures of P-G family. The quantile function,\nasymptotes, shapes, stochastic ordering, moment generating function, order\nstatistics, probability weighted moments and R 'enyi entropy are derived.\nMaximum likelihood estimation with large sample properties is presented. A\nMonte Carlo simulation is used to examine the pattern of the bias and the mean\nsquare error of the maximum likelihood estimators. An illustration of\ncomparison with some of the important sub models of the family in modeling a\nreal data reveals the utility of the proposed family.\n

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