This paper reviews recent research on dependent functional data. After providing an
introduction to functional data analysis, we focus on two types of dependent functional data …

Air quality monitoring is based on pollutants concentration levels, typically recorded in
metropolitan areas. These exhibit spatial and temporal dependence as well as seasonality …

In this paper, a subsampling-based testing procedure for the comparison of the exceedance
distributions of stationary time series is introduced. The proposed testing procedure has a …

Statistical inference of a probability of exceeding a large critical value is studied in the peaks-
over-threshold (POT) approach. The focus is on assessing the performance of the various …

In this work, a fully nonparametric geostatistical approach to estimate threshold exceeding
probabilities is proposed. To estimate the large-scale variability (spatial trend) of the …

Several studies have indicated that the social, economic and other impacts of global
warming can be linked with changes in the frequency and intensity of extreme …

The distribution function of a spatial random process provides the probability that the
variable involved does not exceed a given threshold. Estimation of this function can be …

We model extreme river flow data from five UK rivers with distinct hydrological properties.
The data exhibit significant and complex nonstationarity, which we model using a nonlinear …

A parametric model obtained by fitting a set of data to a function generally uses a procedure
such as maximum likelihood or least squares. In general this will generate the best estimate …

Among the many atmospheric pollutants, fine particles are known to be particularly
damaging to respiratory health, and therefore many efforts are being made worldwide to …