1. Departamento de Estatística , USP , USP, Caixa Postal 66281, Sao Paulo SP, 05315-970, Brazil;2. Departamento de Estatística , UFPB, Cidade Universitária , Jo?o Pessoa PB, 58051-220, Brazil
Abstract:
This paper discusses calibration in functional regression models. Classical and inverse type estimators are considered. First order approximation to the bias and to the mean squared error (MSE) of the estimators are considered. Numerical comparisons seem to indicate that the classical estimator obtained via maximum likelihood estimation performs better than the other estimators considered.