On Underdispersed Count Kernels for Smoothing Probability Mass Functions
Célestin C. Kokonendji,
Sobom M. Somé,
Youssef Esstafa
et al.
Abstract:Only a few count smoothers are available for the widespread use of discrete associated kernel estimators, and their constructions lack systematic approaches. This paper proposes the mean dispersion technique for building count kernels. It is only applicable to count distributions that exhibit the underdispersion property, which ensures the convergence of the corresponding estimators. In addition to the well-known binomial and recent CoM-Poisson kernels, we introduce two new ones such the double Poisson and gam… Show more
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