Performance of methods that separate common and distinct variation in multiple data blocks-Reference-Cited by-同舟云学术

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Performance of methods that separate common and distinct variation in multiple data blocks

Published:2018-10-09 Issue:1 Volume:33 Page:e3085
ISSN:0886-9383
Container-title:Journal of Chemometrics
language:en
Short-container-title:Journal of Chemometrics

Author:

Måge Ingrid¹^ORCID,Smilde Age K.²^ORCID,van der Kloet Frans M.³^ORCID

Affiliation:

1. Department of raw materials and process optimization, Division Food Science; Nofima; Osloveien 1 N-1430 Ås Norway

2. Biosystems Data Analysis; Swammerdam Institute for Life Sciences, University of Amsterdam; Amsterdam The Netherlands

3. Clinical Epidemiology, Biostatistics and Bioinformatics; Amsterdam University Medical Centers; Amsterdam The Netherlands

Funder

Norwegian Levy on Agricultural Products

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cem.3085/fullpdf

Reference35 articles.

1. Canonical analysis of several sets of variables;Kettenring;Biometrica,1971

2. Linear relations among k sets of variables;Geer;Psycometrica,1984

3. Analysis of multiblock and hierarchical PCA and PLS models;Westerhuis;J Chemometr,1998

4. Multimodal data fusion: an overview of methods, challenges, and prospects;Lahat;Proc IEEE,2015

5. Data fusion in metabolomics and proteomics for biomarker discovery. In: Jung K, ed. Statistical Analysis in Proteomics SE - 14;Blanchet;Methods Mol Biol,2016

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