S. Novo Díaz, G. Aneiros Pérez

This package is devoted to estimation or simultaneous estimation and variable selection of several functional semiparametric models with a scalar response. That includes the functional single-index model, the semi-functional partial linear model, and the semi-functional partial linear single-index model. It also contains algorithms for addressing estimation and variable selection in the linear model, the multi-functional partial linear model, and the multi-functional partial linear single-index model when the scalar covariates with linear effects come from the discretization of a curve. In addition, the package has routines for kernel- and kNN-based estimation with Nadaraya-Watson weights of models with a nonparametric component. It also contains functions to compute predictions from all the considered models and estimation procedures.

Keywords: R package, Functional data analysis, Variable selection, Semiparametrics, Multi-functional covariates, Functional single-index model


GT09.NOPAR1 Invited Session. High dimension inference
November 7, 2023  3:30 PM
CC2: Conference Room

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Smooth k-sample tests under left truncation

A. Lago, I. Van Keilegom, J. C. Pardo Fernández, J. de Uña Álvarez

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