Modeling and Analysis of Compositional Data presents a practical and comprehensive
introduction to the analysis of compositional data along with numerous examples to illustrate …

Functional data analysis (FDA) is a statistical framework that allows for the analysis of
curves, images, or functions on higher dimensional domains. The goals of FDA, such as …

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 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 …

Biosensor data have the potential to improve disease control and detection. However, the
analysis of these data under free-living conditions is not feasible with current statistical …

The year 2022 marked 40 years since Aitchison published the article'The statistical analysis
of compositional data'. It is considered to be the foundation of contemporary compositional …

The problem of performing functional linear regression when the response variable is
represented as a probability density function (PDF) is addressed. PDFs are interpreted as …

The advance of sensor and information technologies is leading to data-rich industrial
environments, where large amounts of data are potentially available. This study focuses on …