The aim of this paper is to extend the ideas of generalized additive models for multivariate data (with known or unknown link function) to functional data covariates. The proposed algorithm is a modified version of the local scoring and backfitting algorithms that allows for the nonparametric...

This paper investigates a semi-parametric model for functional data, based on partial linear ideas. A methodology is developped for testing the linear component of such a functional partial linear model. The behavior of the test is studied through some finite simulated samples before being...

Our goal is to predict a scalar value or a group membership from the discretized observation of curves with sharp local features that might vary both vertically and horizontally. To this aim, we propose to combine the use of the nonparametric functional regression estimator developed by Ferraty...

Functional principal components (FPC’s) provide the most important and most extensively used tool for dimension reduction and inference for functional data. The selection of the number, d, of the FPC’s to be used in a specific procedure has attracted a fair amount of attention, and a number...

Economic and financial data often take the form of a collection of curves observed consecutively over time. Examples include, intraday price curves, yield and term structure curves, and intraday volatility curves. Such curves can be viewed as a time series of functions. A fundamental issue that...

Proper assessment of air quality is of paramount importance. Accordingly, authorities in large cities have established air pollution monitoring networks that register levels of the most dangerous pollutants in a number of city locations on an hourly basis. Thus, the dataset including such...

Let (Zi=(Xi,Yi),i∈ZN) be a F×R-valued measurable strictly stationary spatial process, where F is a semi-metric space. We study a kernel estimator of the conditional mode of the univariate response variable Yi given the functional variable Xi. The main aim of this paper is to prove the almost...

Let (Xi,Yi)i=1,…,n be a sequence of stationary ergodic processes valued in F×R, where F is a semi-metric space. We consider the problem of estimating the regression function of Yi given Xi by the robust M-estimation method. The principal aim of this work is to prove the almost complete...

In this article we introduce a new methodology for modeling curves with a dynamic structure, using a non-parametric approach formulated as a state space model. The non-parametric approach is based on the use of penalized splines, represented as a dynamic mixed model. This formulation can capture...