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Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences
Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland
Page: 336
Format: pdf, ePub, mobi, fb2
ISBN: 9781394211210
Publisher: Wiley

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Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland PDF, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Epub, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Read Online, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Audiobook, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland VK, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Kindle, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Epub VK, Analysis of Variance for High-Dimensional Data: Applications in Life, Food, and Chemical Sciences Age K. Smilde, Federico Marini, Johan A. Westerhuis, Kristian Hovde Liland Free Download

Overview
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 perspective Available 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 extensions Applications in metabolomics, microbiome, gene expression, proteomics, food science, sensory science, and chemistry Commercially 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.