The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

We consider nonparametric estimation of the mean and covariance functions for
functional/longitudinal data. Strong uniform convergence rates are developed for estimators …

The aim of this paper is to provide a selected advanced review on semiparametric
regression which is an emergent promising field of researches in functional data analysis …

A polynomial spline estimator is proposed for the mean function of dense functional data
together with a simultaneous confidence band which is asymptotically correct. In addition …

Functional principal component analysis (FPCA) has become the most widely used
dimension reduction tool for functional data analysis. We consider functional data measured …

We investigate a class of partially linear functional additive models (PLFAM) that predicts a
scalar response by both parametric effects of a multivariate predictor and nonparametric …

Motivated by the analysis of imaging data, we propose a novel functional varying-coefficient
single-index model (FVCSIM) to carry out the regression analysis of functional response …

When classification methods are applied to high-dimensional data, selecting a subset of the
predictors may lead to an improvement in the predictive ability of the estimated model, in …

Abstract Let\(X_ {1},\ldots, X_ {n}\) be iid sample in\(\mathbb {R}^{p}\) with zero mean and the
covariance matrix\(\varvec {\Sigma}\). The problem of recovering the projector onto an …

Housing submarkets have been defined by different criteria:(i) similarity in house
attributes;(ii) similarity in hedonic prices; and (iii) substitutability of houses. We show that …