Regression estimation based on Bernstein density copulas∗
نویسندگان
چکیده
The regression function can be expressed in term of copula density and marginal distributions. In this paper, we propose a new method of estimating a regression function using the Bernstein estimator for the copula density and the empirical distributions for the marginal distributions. The method is fully non-parametric and easy to implement. We provide some asymptotic results related to this copula-based regression modeling by showing the almost sure convergence and the asymptotic normality of the estimator by providing the asymptotic variance. Also, we study the finite sample performance of the estimator.
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