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Analysis of Variance for High-dimensional Data: Applications in Life, Food, and Chemical Sciences - Couverture rigide
Synopsis
"This book presents an overview of available methods to analyze high-dimensional data that are obtained through applying an experimental design. This type of of data is often collected in the natural and life sciences, and many methods for data analysis have been developed in recent years. Following an introduction and overview of the basic theory from a mathematical and statistical perspective, the book introduces the available methods and their mutual relationships, including coverage of ASCA, APCA and PC-ANOVA, ASCA, LiMM-PCA and RM-ASCA, PERMANOVA. Various alternative methods and extensions are covered, followed by a thorough review of application in areas including metabolomics, microbiomoe, gene expression, proteomics, food science, sensory science and chemistry. The book concludes with discussions on commercially available and and open-source software for application of these methods."-- Provided by publisher.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Age K. Smilde is Emeritus-Professor of Biosystems Data Analysis at the Swammerdam Institute for Life Sciences at the University of Amsterdam. He also holds a part-time position at the Department of Plant and Environmental Sciences at the University of Copenhagen.
Federico Marini is Professor of Analytical Chemistry at the Department of Chemistry of the University of Rome "La Sapienza".
Johan A. Westerhuis is Assistant Professor at the Swammerdam Institute for Life Sciences, University of Amsterdam, The Netherlands.
Kristian H. Liland is Professor of Statistics at the Faculty of Science and Technology, Norwegian University of Life Sciences, Norway.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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ANALYSIS OF VARIANCE FOR HIGH-DIMENSIONAL DATA: APPLICATIONS IN LIFE, FOOD, AND CHEMICAL SCIENCES
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ANALYSIS OF VARIANCE FOR HIGH-DIMENSIONAL DATA: APPLICATIONS IN LIFE, FOOD, AND CHEMICAL SCIENCES
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Analysis of Variance for High-dimensional Data: Applications in Life, Food, and Chemical Sciences
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Analysis of Variance for High-Dimensional Data
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John Wiley and Sons Inc, 2025
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ISBN 13 : 9781394211210
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Analysis of Variance for High-Dimensional Data: Applications in Life, Food and Chemical Sciences (eng)
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Analysis of Variance for High-dimensional Data: Applications in Life, Food, and Chemical Sciences
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Analysis of Variance for High-Dimensional Data (Hardcover)
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John Wiley & Sons Inc, New York, 2025
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Hardcover. Etat : new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781394211210
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Analysis of Variance for High-Dimensional Data
Edité par
John Wiley and Sons Inc, US, 2025
ISBN 10 : 139421121X
ISBN 13 : 9781394211210
Neuf
Couverture rigide
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : 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. N° de réf. du vendeur LU-9781394211210
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