On Zero-truncated Alternative Hyper-Poisson Distribution and Its Applications
Here we propose a zero-truncated version of the alternative hyper-Poisson distribution of Kumar and Nair[1] and study some of its statistical properties. We derive some of its essential properties such as mean, variance, probability generating function, cumulative distribution function, hazard funct...
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Published in | Bulletin - Calcutta Statistical Association Vol. 74; no. 1; pp. 7 - 26 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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New Delhi, India
SAGE Publications
01.05.2022
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Abstract | Here we propose a zero-truncated version of the alternative hyper-Poisson distribution of Kumar and Nair[1] and study some of its statistical properties. We derive some of its essential properties such as mean, variance, probability generating function, cumulative distribution function, hazard function, an expression for its factorial moments, raw moments and recursion formulae for its probabilities, raw moments and factorial moments. The method of moments and method of maximum likelihood estimation have been discussed for estimating the parameters of the proposed distribution. To check the suitability of the proposed model it has been applied to certain real-life data sets and has shown that it provides a good fitting to the data sets under consideration. Method of generalized likelihood ratio test is employed for examining the significance of the parameter and a brief simulation study is carried out for verifying the efficiency of the moment and maximum likelihood estimators of the parameters of the distribution.
AMS subject classification: 60E05; 60E10; 33C20 |
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AbstractList | Here we propose a zero-truncated version of the alternative hyper-Poisson distribution of Kumar and Nair
[ 1 ]
and study some of its statistical properties. We derive some of its essential properties such as mean, variance, probability generating function, cumulative distribution function, hazard function, an expression for its factorial moments, raw moments and recursion formulae for its probabilities, raw moments and factorial moments. The method of moments and method of maximum likelihood estimation have been discussed for estimating the parameters of the proposed distribution. To check the suitability of the proposed model it has been applied to certain real-life data sets and has shown that it provides a good fitting to the data sets under consideration. Method of generalized likelihood ratio test is employed for examining the significance of the parameter and a brief simulation study is carried out for verifying the efficiency of the moment and maximum likelihood estimators of the parameters of the distribution.
AMS subject classification: 60E05; 60E10; 33C20 Here we propose a zero-truncated version of the alternative hyper-Poisson distribution of Kumar and Nair[1] and study some of its statistical properties. We derive some of its essential properties such as mean, variance, probability generating function, cumulative distribution function, hazard function, an expression for its factorial moments, raw moments and recursion formulae for its probabilities, raw moments and factorial moments. The method of moments and method of maximum likelihood estimation have been discussed for estimating the parameters of the proposed distribution. To check the suitability of the proposed model it has been applied to certain real-life data sets and has shown that it provides a good fitting to the data sets under consideration. Method of generalized likelihood ratio test is employed for examining the significance of the parameter and a brief simulation study is carried out for verifying the efficiency of the moment and maximum likelihood estimators of the parameters of the distribution. AMS subject classification: 60E05; 60E10; 33C20 |
Author | Kumar, C. Satheesh Abraham, Emil Ninan |
Author_xml | – sequence: 1 givenname: C. Satheesh surname: Kumar fullname: Kumar, C. Satheesh email: drcsatheeshkumar@gmail.com – sequence: 2 givenname: Emil Ninan surname: Abraham fullname: Abraham, Emil Ninan email: emilninanabraham@gmail.com |
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Keywords | Confluent hypergeometric function maximum likelihood estimation Stirling numbers of the second kind GLRT simulation |
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References | Puig 2003; 98 Kiani 2020 Shanker, Shukla 2017; 3 Metropolis, Ulam 1949; 44 Kumar, Nair 2012; 72 Chib, Greenberg 1995; 49 Kumar, Abraham 2020; 80 Shanker, Shukla 2021; 13 Rama, Simon 2018; 2 Borah, Saikia 2017; 5 Tian, Ding, Liu 2019; 34 Kozubowski, Panorska, Forister 2015; 26 Kumar, Nair 2013; 28 Metropolis, Rosenbluth, Rosenbluth, Teller 1953; 21 Shukla, Shanker, Tiwari 2020; 64 Kumar, Nair 2013; 33 Shanker, Hagos, Sujatha 2015; 2 bibr8-00080683221094170 bibr14-00080683221094170 bibr20-00080683221094170 Kumar CS (bibr1-00080683221094170) 2012; 72 bibr5-00080683221094170 Kumar CS (bibr10-00080683221094170) 2020; 80 Shukla KK (bibr11-00080683221094170) 2020; 64 bibr2-00080683221094170 Rama S (bibr16-00080683221094170) 2018; 2 Shanker R (bibr12-00080683221094170) 2021; 13 Kumar CS (bibr4-00080683221094170) 2013; 33 Riordan J. (bibr13-00080683221094170) 1968 bibr19-00080683221094170 Shanker R (bibr17-00080683221094170) 2015; 2 bibr15-00080683221094170 Abramowitz M (bibr3-00080683221094170) 1965 Borah M (bibr7-00080683221094170) 2017; 5 bibr9-00080683221094170 Shanker R (bibr18-00080683221094170) 2017; 3 bibr6-00080683221094170 Chib S (bibr21-00080683221094170) 1995; 49 |
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