Article ID Journal Published Year Pages File Type
1147954 Journal of Statistical Planning and Inference 2012 12 Pages PDF
Abstract

This work deals with a semiparametric estimation of a count regression function m that can be represented as a product of an unknown discrete parametric function r   and an unknown discrete “smooth” function ωω. We propose an estimation procedure in two steps: first, we construct an approximation r^ of r  , then we use a discrete associated kernel method to estimate nonparametrically the multiplicative correction factor ω=m/r^. The asymptotic and small-sample properties of the proposed estimator are investigated. Its comparison with the classical Nadaraya–Watson type count regression estimator shows that an improvement in terms of bias is achieved.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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