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ON A WIDE CLASS OF GENERALIZED GEOMETRIC DISTRIBUTION FOR OVER AND UNDER DISPERSED DATA SETS

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  • C. Satheesh Kumar,
  • S Harisankar
C. Satheesh Kumar
Department of Statistics, University of Kerala, Thiruvananthapuram, India
DOI: https://doi.org/10.36253/ijas-16753

Published 2025-09-25

Keywords

  • Generalized Likelihood Ratio Test,
  • Model Selection,
  • Maximum Likelihood Estimation,
  • Probability generating function,
  • Simulation

How to Cite

Kumar, C. S., & Harisankar, S. (2025). ON A WIDE CLASS OF GENERALIZED GEOMETRIC DISTRIBUTION FOR OVER AND UNDER DISPERSED DATA SETS. Italian Journal of Applied Statistics. https://doi.org/10.36253/ijas-16753

Copyright (c) 2024 C. Satheesh Kumar, S Harisankar

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In this paper, a wide class of generalized geometric distribution is introduced and we name this class of distributions as “the alpha generalized geometric distribution (AGGD)". Several important distributions are obtained as a special cases of this proposed model. Important distributional properties such as generating functions, moments, recursive relations of the proposed distribution are examined. Parameter estimation using maximum likelihood is discussed. Three well-known data sets, having long tails, are analyzed and the results of fitting by various models are provided. Further, the generalized likelihood ratio test procedure is considered for testing the significance of the parameters of the GGD. Finally, performance of the different estimation methods are compared by means of a Monte Carlo simulation.

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