Some Asymptotic Theory for Functional Regression and Classification

Abstract EN

Exploiting an expansion for analytic functions of operators, the asymptotic distribution of an estimator of the functional regression parameter is obtained in a rather simple way; the result is applied to testing linear hypotheses.

The expansion is also used to obtain a quick proof for the asymptotic optimality of a functional classification rule, given Gaussian populations.