Parameter Estimation for Discrete Distributions by Generalized Hellinger-Type Divergence Based on Probability Generating Function |
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| Authors: | S Z Sim |
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| Institution: | Institute of Mathematical Sciences , University of Malaya , Kuala Lumpur, Malaysia |
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| Abstract: | This article considers a probability generating function-based divergence statistic for parameter estimation. The performance and robustness of the proposed statistic in parameter estimation is studied for the negative binomial distribution by Monte Carlo simulation, especially in comparison with the maximum likelihood and minimum Hellinger distance estimation. Numerical examples are given as illustration of goodness of fit. |
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| Keywords: | Maximum likelihood Mean square error Minimum Hellinger distance Monte Carlo Negative binomial distribution Outliers Robustness |
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