Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147954 | Journal of Statistical Planning and Inference | 2012 | 12 Pages |
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
Authors
Belkacem Abdous, Célestin C. Kokonendji, Tristan Senga Kiessé,