Cell-wise robust covariance estimation for compositions, with application to geochemical data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F23%3A73621519" target="_blank" >RIV/61989592:15310/23:73621519 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0375674223001462" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0375674223001462</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.gexplo.2023.107299" target="_blank" >10.1016/j.gexplo.2023.107299</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cell-wise robust covariance estimation for compositions, with application to geochemical data

Popis výsledku v původním jazyce

Cell-wise outliers are outliers in single entries of a compositional data matrix, and they can lead to a certain bias in the statistical analysis. Traditional row-wise robust methods downweight outlying observations for the estimation, independent of how many or which cells of an observation are contaminated. Cell-wise robustness still makes use of the information contained in non-contaminated cells. Here, cell-wise robustness is used for the estimation of the variation and the covariance matrix. For higher dimensional data also a regularized estimator is introduced. The advantages of the cell-wise robust estimators are demonstrated in simulation experiments and in a geochemistry application in the context of clustering and principal component analysis.

Název v anglickém jazyce

Cell-wise robust covariance estimation for compositions, with application to geochemical data

Popis výsledku anglicky

Cell-wise outliers are outliers in single entries of a compositional data matrix, and they can lead to a certain bias in the statistical analysis. Traditional row-wise robust methods downweight outlying observations for the estimation, independent of how many or which cells of an observation are contaminated. Cell-wise robustness still makes use of the information contained in non-contaminated cells. Here, cell-wise robustness is used for the estimation of the variation and the covariance matrix. For higher dimensional data also a regularized estimator is introduced. The advantages of the cell-wise robust estimators are demonstrated in simulation experiments and in a geochemistry application in the context of clustering and principal component analysis.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GF22-15684L" target="_blank" >GF22-15684L: Zobecněná relativní data a robustnost v Bayesových prostorech</a><br>

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

JOURNAL OF GEOCHEMICAL EXPLORATION

ISSN

0375-6742

e-ISSN

1879-1689

Svazek periodika

253

Číslo periodika v rámci svazku

OCT

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

"107299-1"-"107299-11"

Kód UT WoS článku

001076549100001

EID výsledku v databázi Scopus

2-s2.0-85169070370