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 …

Contents. Some journals that regularly publish papers on environmental analysis or related
topics were searched directly. The review focuses on recent advances and current trends in …

Abstract Air Quality Monitoring Networks (AQMNs) are composed by a number of stations,
which are typically classified as urban, suburban or rural, and background, industrial or …

We propose a novel model selection algorithm based on a penalized maximum likelihood
estimator (PMLE) for functional hidden dynamic geostatistical models (f-HDGM). These …

In this paper, following a fuzzy approach and adopting an autoregressive parameterization,
we propose a robust clustering model for classifying time series. In particular, by adopting a …

Interval-valued functional clustering is a novel approach for functional data analysis where
each observation is represented by an interval. Existing interval-valued functional clustering …

The observation sites that make up air quality monitoring networks can have very different
characteristics (topography, climatology, distance to emission sources, etc), which are …

This paper investigates the hypothesis test of the parametric component in partial functional
linear regression. We propose a test procedure based on the residual sums of squares …

Fuzzy clustering enables the simultaneous membership of objects in two or more clusters.
This is particularly pertinent where time series are concerned, because very often patterns of …

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks
(AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns …