[Forum SIS] Course ISI-ERS "An Introduction to Functional Data Analysis for Density Functions in Bayes spaces"

[Alessandra Menafoglio]

We cordially invite you to the short course "An Introduction to Functional Data Analysis for Density Functions in Bayes spaces”, which will be held on 29-30 April 2021, both days from 14:00 alle 17:00 (GMT+2).

The course is part of the initiatives of the International Statistical Institute (ISI-ERS). It aims to provide participants with an overview on the models and methods today available for the analysis of distributional data (e.g., probability densities) by using the geometry of Bayes spaces.

Further information on the course is available at: https://iasc-isi.org/events/iasc-ers-course-an-introduction-to-functional-data-analysis-for-density-functions-in-bayes-spaces/ <https://iasc-isi.org/events/iasc-ers-course-an-introduction-to-functional-data-analysis-for-density-functions-in-bayes-spaces/>

Participation to the webinars is free of charge, but registration is requested using the link below:
https://register.gotowebinar.com/register/8667082239416059148 <https://register.gotowebinar.com/register/8667082239416059148>

Best regards,

Alessandra Menafoglio
Karel Hron
Jitka Machalova


**Abstract**
The analysis of distributional data (probability density functions or histogram data) has recently gained increasing attention in the applications. Distributional data are often observed by themselves, or as result of aggregation of large streams of data. The course will provide an introduction to the analysis of these data using a Functional Data Analysis (FDA) approach, grounded on the perspective of Bayes spaces. These spaces are mathematical spaces whose points are densities (or, more generally, measures), which generalize to the FDA setting the Aitchison simplex for multivariate compositional data. The course will give an overview of the theory of Bayes spaces, as well as of statistical methods developed in this setting. All the methods will be illustrated through examples from real case studies.

—
Alessandra Menafoglio
MOX - Dept. of Mathematics
Politecnico di Milano
Piazza Leonardo da Vinci, 32,
20133 Milan - Italy
Phone: +39 02 2399 4642
Email: alessandra.menafoglio a polimi.it

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