Estimation of Generalized Poisson Distribution by the Method of Weighted Discrepancies

Felix Famoye and Carl M.-S Lee
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Felix Famoye: Central Michigan University, Department of Mathematics
Carl M.-S Lee: Central Michigan University, Department of Mathematics

A chapter in Computing Science and Statistics, 1992, pp 332-335 from Springer

Abstract: Abstract The generalized Poisson distribution (GPD) has been found to be a very versatile discrete distribution with applications in various areas of study such as engineering, manufacturing, survival analysis, genetic and branching processes. In this paper, we study the estimation of generalized Poisson distribution by the method of weighted discrepancies between observed and expected frequencies. The methods of maximum likelihood, minimum chi-square and the minimum discrimination information estimation are special cases of the weighted discrepancies method. It is found that the weighted discrepancies method is better than the minimum chi-square method and compares very well with the maximum likelihood method.

Keywords: Weighted Discrepancy; Moment Estimate; Generalize Poisson Distribution; Discrepancy Estimation Method; Summer Fellowship (search for similar items in EconPapers)
Date: 1992
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-2856-1_48

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DOI: 10.1007/978-1-4612-2856-1_48

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