Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

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 …

Introduction to Functional Data Analysis provides a concise textbook introduction to the field.
It explains how to analyze functional data, both at exploratory and inferential levels. It also …

A common goal in modeling and data mining is to determine, based on sample data,
whether or not a change of some sort has occurred in a quantity of interest. The study of …

Previous research has examined resting electroencephalographic (EEG) data to explore
brain activity related to meditation. However, previous research has mostly examined power …

Methodology is proposed to uncover structural breaks in functional data that is 'fully
functional'in the sense that it does not rely on dimension reduction techniques. A thorough …

We introduce methods and theory for functional or curve time series with long-range
dependence. The temporal sum of the curve process is shown to be asymptotically normally …

For a functional ARMA (p, q) process an approximating vector model, based on functional
PCA, is presented. Sufficient conditions are given for the existence of a stationary solution to …

We propose a nonparametric two-sample test procedure based on Maximum Mean
Discrepancy (MMD) for testing the hypothesis that two samples of functions have the same …

Age-specific mortality rates are often disaggregated by different attributes, such as sex, state,
and ethnicity. Forecasting age-specific mortality rates at the national and sub-national levels …