Modern studies from a variety of fields record multiple functional observations according to
either multivariate, longitudinal, spatial, or time series designs. We refer to such data as …

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 …

This book presents recently developed statistical methods and theory required for the
application of the tools of functional data analysis to problems arising in geosciences …

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 …

We propose an extensive framework for additive regression models for correlated functional
responses, allowing for multiple partially nested or crossed functional random effects with …

The paper is concerned with inference based on the mean function of a functional time
series. We develop a normal approximation for the functional sample mean and then focus …

A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space Page 1
Electronic Journal of Statistics Vol. 7 (2013) 2209–2240 ISSN: 1935-7524 DOI: 10.1214/13-EJS843 …

We introduce a simple and interpretable model for functional data analysis for situations
where the observations at each location are functional rather than scalar. This new …

This paper presents a simultaneous localization and map** (SLAM) method that utilizes
the measurement of ambient magnetic fields present in all indoor environments. In this …

We consider dependent functional data that are correlated because of a longitudinal‐based
design: each subject is observed at repeated times and at each time, a functional …