Functional data analysis (FDA) involves the analysis of data whose ideal units of
observation are functions defined on some continuous domain, and the observed data …

With the advance of modern technology, more and more data are being recorded
continuously during a time interval or intermittently at several discrete time points. These are …

Background Incident cardiovascular disease (CVD) increases with increasing low-density
lipoprotein cholesterol (LDL-C) concentration and exposure duration. Area under the LDL-C …

Figure 1.1 provides a prototype for the type of data that we shall consider. It shows the
heights of 10 girls measured at a set of 31 ages in the Berkeley Growth Study (Tuddenham …

Semiparametric regression is concerned with the flexible incorporation of non-linear
functional relationships in regression analyses. Any application area that benefits from …

We propose a nonparametric method to perform functional principal components analysis
for the case of sparse longitudinal data. The method aims at irregularly spaced longitudinal …

This advanced text focuses on the uses of distance sampling to estimate the density and
abundance of biological populations. It addresses new methodologies, new technologies …

With contributions from some of the most prominent researchers in the field, this carefully
edited collection provides a clear, comprehensive, and unified overview of recent …

From sparse to dense functional data and beyond Page 1 The Annals of Statistics 2016, Vol.
44, No. 5, 2281–2321 DOI: 10.1214/16-AOS1446 © Institute of Mathematical Statistics, 2016 …

We propose nonparametric methods for functional linear regression which are designed for
sparse longitudinal data, where both the predictor and response are functions of a covariate …