Bias-reduced maximum likelihood estimation of the zero-inflated Poisson distribution

Jacob Schwartz and David Giles

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 2, 465-478

Abstract: We investigate the small-sample quality of the maximum likelihood estimators (MLE) of the parameters of a zero-inflated Poisson distribution (ZIP). The finite-sample bias of the MLE is determined to O(n−1) using an analytic bias-reduction methodology based on the work of Cox and Snell (1968) and Cordeiro and Klein (1994). Monte Carlo simulations show that the MLEs have very small percentage biases for this distribution, but the analytic bias-reduction methods essentially eliminate the bias without adversely affecting the mean-squared errors of the estimators. The analytic adjustment compares favorably with the parametric bootstrap bias-corrected estimator, in terms of bias reduction itself, as well as with respect to mean-squared error and Pitman’s nearness measure.

Date: 2016
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Citations: View citations in EconPapers (6)

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DOI: 10.1080/03610926.2013.824590

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