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 …

The series aims to: present current and emerging innovations in GIScience; describe new
and robust GIScience methods for use in transdisciplinary problem solving and decision …

The Wasserstein metric, Wasserstein–Fréchet mean, simulation results and additional
proofs. The supplementary material includes additional discussion on the Wasserstein …

The log-ratio approach to compositional data (CoDa) analysis has now entered a mature
phase. The principles and statistical tools introduced by J. Aitchison in the eighties have …

Recent developments in the probabilistic and statistical analysis of probability density
functions are reviewed. Density functions are treated as data objects for which suitable …

Probability density functions are frequently used to characterize the distributional properties
of large-scale database systems. As functional compositions, densities primarily carry …

A Bayes linear space is a linear space of equivalence classes of proportional σ‐finite
measures, including probability measures. Measures are identified with their density …

We consider the problem of predicting the spatial field of particle-size curves (PSCs) from a
sample observed at a finite set of locations within an alluvial aquifer near the city of …

This paper is concerned with the forecasting of probability density functions. Density
functions are nonnegative and have a constrained integral, and thus do not constitute a …

Data consisting of time‐indexed distributions of cross‐sectional or intraday returns have
been extensively studied in finance, and provide one example in which the data atoms …