Functional data analysis is a field of growing importance in Statistics. In particular, the
functional linear model with scalar response is surely the model that has attracted more …

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 …

Functional data analysis (FDA), which is a branch of statistics on modeling infinite
dimensional random vectors resided in functional spaces, has become a major research …

Functional data analysis has been a popular statistical research topic for the past three
decades. Functional data are often obtained by observing a number of subjects over time …

Functional data often arise from measurements on fine time grids and are obtained by
separating an almost continuous time record into natural consecutive intervals, for example …

We study in this paper a smoothness regularization method for functional linear regression
and provide a unified treatment for both the prediction and estimation problems. By …

The paper considers functional linear regression, where scalar responses Y 1,…, Y n are
modeled in dependence of random functions X 1,…, X n. We propose a smoothing splines …

It is frequently the case that a response will be related to both a vector of finite length and a
function-valued random variable as predictor variables. In this paper, we propose new …

We propose a multivariate functional linear regression (mFLR) approach to analysis and
prediction of multivariate functional data in cases in which both the response and predictor …

We propose a multistage testing procedure to determine the order p of a functional
autoregressive process, FAR (p). At its core is the representation of the FAR (p) process as a …