Compositional covariance shrinkage and regularised partial correlations

We propose an estimation procedure for covariation in wide compositional data sets. For compositions, widely-used logratio variables are interdependent due to a common reference. Logratio uncorrelated compositions are linearly independent before the unitsum constraint is imposed. We show how they ar...

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Detalles Bibliográficos
Autores: Jin, Suzanne, Notredame, Cedric, Erb, Ionas
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/60812
Acceso en línea:http://hdl.handle.net/10230/60812
http://dx.doi.org/10.57645/20.8080.02.8
Access Level:acceso abierto
Palabra clave:Compositional covariance structure
Logratio analysis
Partial correlation
James-Stein shrinkage
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spelling Compositional covariance shrinkage and regularised partial correlationsJin, SuzanneNotredame, CedricErb, IonasCompositional covariance structureLogratio analysisPartial correlationJames-Stein shrinkageWe propose an estimation procedure for covariation in wide compositional data sets. For compositions, widely-used logratio variables are interdependent due to a common reference. Logratio uncorrelated compositions are linearly independent before the unitsum constraint is imposed. We show how they are used to construct bespoke shrinkage targets for logratio covariance matrices and test a simple procedure for partial correlation estimates on both a simulated and a single-cell gene expression data set. For the underlying counts, different zero imputations are evaluated. The partial correlation induced by the closure is derived analytically. Data and code are available from GitHub.Statistical Institute of Catalonia202420242023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/60812http://dx.doi.org/10.57645/20.8080.02.8reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésSORT-Statistics and Operations Research Transactions. 2023;47(2):245-68This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0).http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/608122026-06-12T07:21:37Z
dc.title.none.fl_str_mv Compositional covariance shrinkage and regularised partial correlations
title Compositional covariance shrinkage and regularised partial correlations
spellingShingle Compositional covariance shrinkage and regularised partial correlations
Jin, Suzanne
Compositional covariance structure
Logratio analysis
Partial correlation
James-Stein shrinkage
title_short Compositional covariance shrinkage and regularised partial correlations
title_full Compositional covariance shrinkage and regularised partial correlations
title_fullStr Compositional covariance shrinkage and regularised partial correlations
title_full_unstemmed Compositional covariance shrinkage and regularised partial correlations
title_sort Compositional covariance shrinkage and regularised partial correlations
dc.creator.none.fl_str_mv Jin, Suzanne
Notredame, Cedric
Erb, Ionas
author Jin, Suzanne
author_facet Jin, Suzanne
Notredame, Cedric
Erb, Ionas
author_role author
author2 Notredame, Cedric
Erb, Ionas
author2_role author
author
dc.subject.none.fl_str_mv Compositional covariance structure
Logratio analysis
Partial correlation
James-Stein shrinkage
topic Compositional covariance structure
Logratio analysis
Partial correlation
James-Stein shrinkage
description We propose an estimation procedure for covariation in wide compositional data sets. For compositions, widely-used logratio variables are interdependent due to a common reference. Logratio uncorrelated compositions are linearly independent before the unitsum constraint is imposed. We show how they are used to construct bespoke shrinkage targets for logratio covariance matrices and test a simple procedure for partial correlation estimates on both a simulated and a single-cell gene expression data set. For the underlying counts, different zero imputations are evaluated. The partial correlation induced by the closure is derived analytically. Data and code are available from GitHub.
publishDate 2023
dc.date.none.fl_str_mv 2023
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/60812
http://dx.doi.org/10.57645/20.8080.02.8
url http://hdl.handle.net/10230/60812
http://dx.doi.org/10.57645/20.8080.02.8
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv SORT-Statistics and Operations Research Transactions. 2023;47(2):245-68
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Statistical Institute of Catalonia
publisher.none.fl_str_mv Statistical Institute of Catalonia
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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