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 …

As high-dimensional and high-frequency data are being collected on a large scale, the
development of new statistical models is being pushed forward. Functional data analysis …

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

Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a
complete function is observed for each individual give rise to functional data. In this work we …

Spatio-temporal statistical models are increasingly being used across a wide variety of
scientific disciplines to describe and predict spatially-explicit processes that evolve over …

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 …

Functional data featured by a spatial dependence structure occur in many environmental
sciences when curves are observed, for example, along time or along depth. Recently, some …

The electroencephalography (EEG) data created in event‐related potential (ERP)
experiments have a complex high‐dimensional structure. Each stimulus presentation, or …

We review recent advances in Object Oriented Spatial Statistics, a system of ideas,
algorithms and methods that allows the analysis of high dimensional and complex data …

Epilepsy is one of the leading neurological diseases in the world, affecting approximately 70
million of the world's population and often results in early mortality if not properly managed …