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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Condition: New. pp. 256 1st edition NO-PA16APR2015-KAP.
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Analysis of Variance for High-dimensional Data : Applications in Life, Food, and Chemical Sciences
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 256.
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Condition: As New. Unread book in perfect condition.
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Condition: New. pp. 256.
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Analysis of Variance for High-dimensional Data : Applications in Life, Food, and Chemical Sciences
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Analysis of Variance for High-Dimensional Data
Language: English
Published by John Wiley and Sons Inc, US, 2025
ISBN 10: 139421121X ISBN 13: 9781394211210
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. Overview of methods for analyzing high-dimensional experimental data, including theory, methodologies, and applications Analysis of Variance for High-Dimensional Data summarizes all the methods to analyze high-dimensional data that are obtained through applying an experimental design in the life, food, and chemical sciences, especially those developed in recent years. Written by international experts who lead development in the field, Analysis of Variance for High-Dimensional Data includes information on: Basic and established theories on linear models from a mathematical and statistical perspectiveAvailable methods and their mutual relationships, including coverage of ASCA, APCA, PC-ANOVA, ASCA+, LiMM-PCA and RM-ASCA+, and PERMANOVA, as well as various alternative methods and extensionsApplications in metabolomics, microbiome, gene expression, proteomics, food science, sensory science, and chemistryCommercially available and open-source software for application of these methods Analysis of Variance for High-Dimensional Data is an essential reference for practitioners involved in data analysis in the natural sciences, including professionals working in chemometrics, bioinformatics, data science, statistics, and machine learning. The book is valuable for developers of new methods in high dimensional data analysis.
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Hardcover. Condition: Brand New. 256 pages. 7.36x9.96x10.31 inches. In Stock.
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Analysis of Variance for High-Dimensional Data
Language: English
Published by John Wiley and Sons Inc, US, 2025
ISBN 10: 139421121X ISBN 13: 9781394211210
Hardback. Condition: New. Overview of methods for analyzing high-dimensional experimental data, including theory, methodologies, and applications Analysis of Variance for High-Dimensional Data summarizes all the methods to analyze high-dimensional data that are obtained through applying an experimental design in the life, food, and chemical sciences, especially those developed in recent years. Written by international experts who lead development in the field, Analysis of Variance for High-Dimensional Data includes information on: Basic and established theories on linear models from a mathematical and statistical perspectiveAvailable methods and their mutual relationships, including coverage of ASCA, APCA, PC-ANOVA, ASCA+, LiMM-PCA and RM-ASCA+, and PERMANOVA, as well as various alternative methods and extensionsApplications in metabolomics, microbiome, gene expression, proteomics, food science, sensory science, and chemistryCommercially available and open-source software for application of these methods Analysis of Variance for High-Dimensional Data is an essential reference for practitioners involved in data analysis in the natural sciences, including professionals working in chemometrics, bioinformatics, data science, statistics, and machine learning. The book is valuable for developers of new methods in high dimensional data analysis.
