The Generalized Poisson Count Technique and its Statistical Inference

WU Qin; LIU Yin; RUAN Jian

doi:10.6054/j.jscnun.2019109

Journal of South China Normal University (Natural Science Edition) > 2019 > 51(6): 107-110. > DOI: 10.6054/j.jscnun.2019109

WU Qin, LIU Yin, RUAN Jian. The Generalized Poisson Count Technique and its Statistical Inference[J]. Journal of South China Normal University (Natural Science Edition), 2019, 51(6): 107-110. DOI: 10.6054/j.jscnun.2019109

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The Generalized Poisson Count Technique and its Statistical Inference

WU Qin^1, ,,
LIU Yin²,
RUAN Jian³

1.
School of Mathematical Sciences, South China Normal University, Guangzhou 510631, China
2.
School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China
3.
Zhongshan Haotou Middle School, Zhongshan 528437, China

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Received Date: January 09, 2019
Available Online: March 21, 2021

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Abstract

Abstract

Based on the Generalized Poisson distribution, the Generalized Poisson Count Technique is introduced to solve the over-dispersion and under-dispersion in the Poisson Item Count Technique. For the statistical inference, the iterative algorithm using EM algorithm and MM algorithm is studied to calculate the maximum likelihood estimate in the model by introducing the missing data and constructing the substitution function. Furthermore, in the simulation, the bias of the estimate is presented and the simulation results are discussed to find effective information.
- Generalized Poisson distribution,
- EM algorithm,
- MM algorithm,
- parameter estimation,
- simulation

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References

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