Discrete Beta-Type Models
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A more interpretable parameterization of a beta density is the starting point to propose an analogous discrete beta (d. b. ) distribution assuming values on a finite set. Thus a smooth estimator using d. b. kernels is considered. By construction, it is both well-defined and free of boundary bias. Taking advantage of the discrete nature of the data, a technique of smoothing parameter selection is also proposed in moderate-to-large samples. Finally, a real data set is analyzed in order to appreciate the advantages of this nonparametric proposal.
KeywordsBeta Distribution Smoothing Parameter Kernel Estimator Beta Density Interpretable Parameterization
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- Punzo, A., & Zini, A. (2008). Discrete approximations of continuous and mixed measures on a closed interval. Technical Report 160, Universit di Milano-Bicocca, Dipartimento di Metodi Quantitativi per le Scienze Economiche e Aziendali.Google Scholar