Publication type: Conference other
Type of review: Not specified
Title: Functional data analysis in Bayes spaces with an application to spatio-temporal population data
Authors: Templ, Matthias
et. al: No
Proceedings: uRos 2020 Abstracts
Conference details: Use of R in Official Statistics 2020 : 8th international conference, virtual, 2-4 December 2020
Issue Date: 2020
Publisher / Ed. Institution: Statistik Austria
Language: English
Subjects: Functional data analysis; Compositional data analysis; Probability density functions
Subject (DDC): 005: Computer programming, programs and data
Abstract: Probability density functions are frequently used to characterize the distributional properties of large-scale database systems. As functional compositions, densities carry primarily relative information. As such, standard methods of functional data analysis (FDA) are not appropriate for their statistical processing and thus a compositional alternative is proposed. The aim of this presentation is to outline a concise methodology for functional principal component analysis of densities based on the geometry of the Bayes space B2 of functional compositions. Advances of the proposed approach are demonstrated using a real-world example of population pyramids in Upper Austria. For compositional analysis we also introduce the R package robCompositions.
Further description: Keynote
URI: https://uros.hopto.org/
https://digitalcollection.zhaw.ch/handle/11475/22002
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in collections:Publikationen School of Engineering

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