Independent Component Analysis for Compositional Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73609685" target="_blank" >RIV/61989592:15310/21:73609685 - isvavai.cz</a>

Výsledek na webu

<a href="https://obd.upol.cz/id_publ/333189571" target="_blank" >https://obd.upol.cz/id_publ/333189571</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-73249-3_27" target="_blank" >10.1007/978-3-030-73249-3_27</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Independent Component Analysis for Compositional Data

Popis výsledku v původním jazyce

Compositional data represent a specific family of multivariate data, where the information of interest is contained in the ratios between parts rather than in absolute values of single parts. The analysis of such specific data is challenging as the application of standard multivariate analysis tools on the raw observations can lead to spurious results. Hence, it is appropriate to apply certain transformations prior to further analysis. One popular multivariate data analysis tool is independent component analysis. Independent component analysis aims to find statistically independent components in the data and as such might be seen as an extension to principal component analysis. In this paper, we examine an approach of how to apply independent component analysis on compositional data by respecting the nature of the latter and demonstrate the usefulness of this procedure on a metabolomics dataset.

Název v anglickém jazyce

Independent Component Analysis for Compositional Data

Popis výsledku anglicky

Compositional data represent a specific family of multivariate data, where the information of interest is contained in the ratios between parts rather than in absolute values of single parts. The analysis of such specific data is challenging as the application of standard multivariate analysis tools on the raw observations can lead to spurious results. Hence, it is appropriate to apply certain transformations prior to further analysis. One popular multivariate data analysis tool is independent component analysis. Independent component analysis aims to find statistically independent components in the data and as such might be seen as an extension to principal component analysis. In this paper, we examine an approach of how to apply independent component analysis on compositional data by respecting the nature of the latter and demonstrate the usefulness of this procedure on a metabolomics dataset.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Advances in Contemporary Statistics and Econometrics, Festschrift in Honor of Christine Thomas-Agnan

ISBN

978-3-030-73248-6

Počet stran výsledku

21

Strana od-do

525-545

Počet stran knihy

710

Název nakladatele

Springer

Místo vydání

Cham

Kód UT WoS kapitoly

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