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"Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.

Multivariate analysis. --- Research. --- Biology --- Health & Biological Sciences --- Biology - General --- Chemometrics. --- Chemistry, Analytic --- Mathematics --- Measurement --- Statistical methods --- Bioinformatics. --- Chemistry. --- Statistics. --- Computer Applications in Chemistry. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Computer Appl. in Life Sciences. --- Data processing. --- Chemistry --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Physical sciences --- Data processing --- Chemoinformatics. --- Statistics . --- Bioinformatics . --- Computational biology . --- Bioinformatics --- Chemical informatics --- Chemiinformatics --- Chemoinformatics --- Chemistry informatics --- Computational chemistry --- Computational biology. --- R (Computer program language). --- GNU-S (Computer program language) --- Domain-specific programming languages

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Chemometrie. --- Basic Sciences. Chemistry -- Analytical Chemistry

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This book offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection). It also includes a special section discussing several more specific topics in the area of chemometrics, such as outlier detection, and biomarker identification. The corresponding R code is provided for all the examples in the book; and scripts, functions and data are available in a separate R package. This second revised edition features not only updates on many of the topics covered, but also several sections of new material (e.g., on handling missing values in PCA, multivariate process monitoring and batch correction). .

Statistical science --- Qualitative chemical analysis --- Quantitative chemical analysis --- Biomathematics. Biometry. Biostatistics --- analytische chemie --- bio-informatica --- statistiek

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Statistical science --- Qualitative chemical analysis --- Quantitative chemical analysis --- Biomathematics. Biometry. Biostatistics --- analytische chemie --- bio-informatica --- statistiek