activity
20182021
most citedKriging Riemannian Data via Random Domain Decompositions

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ME2021

A new class of -transformations for the spatial analysis of Compositional Data

Lucia Clarotto, Denis Allard, Alessandra Menafoglio

Georeferenced compositional data are prominent in many scientific fields and in spatial statistics. This work addresses the problem of proposing models and methods to analyze and p…

stat.AP2021

Social and material vulnerability in the face of seismic hazard: an analysis of the Italian case

Oleksandr Didkovskyi, Giovanni Azzone, Alessandra Menafoglio +1

The assessment of the vulnerability of a community endangered by seismic hazard is of paramount importance for planning a precision policy aimed at the prevention and reduction of…

math.ST2020

Bivariate Densities in Bayes Spaces: Orthogonal Decomposition and Spline Representation

Karel Hron, Jitka Machalová, Alessandra Menafoglio

A new orthogonal decomposition for bivariate probability densities embedded in Bayes Hilbert spaces is derived. It allows one to represent a density into independent and interactiv…

stat.ME2020

A novel dowscaling procedure for compositional data in the Aitchison geometry with application to soil texture data

Federico Gatti, Alessandra Menafoglio, Niccolò Togni +4

In this work, we present a novel downscaling procedure for compositional quantities based on the Aitchison geometry. The method is able to naturally consider compositional constrai…

math.ST2019

Changing reference measure in Bayes spaces with applications to functional data analysis

R. Talska, A. Menafoglio, K. Hron +2

Probability density functions (PDFs) can be understood as continuous compositions by the theory of Bayes spaces. The origin of a Bayes space is determined by a given reference meas…

stat.ME20181 cited

Kriging Riemannian Data via Random Domain Decompositions

Alessandra Menafoglio, Davide Pigoli, Piercesare Secchi

Data taking value on a Riemannian manifold and observed over a complex spatial domain are becoming more frequent in applications, e.g. in environmental sciences and in geoscience.…