Introduction to Multivariate Statistical Analysis in Chemometrics

Using formal descriptions, graphical illustrations, practical examples, and software tools, this introduction presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. Some of the statistical methods discussed include principal component analysis, regression analysis, classification methods, and clustering. Written by a chemometrician and a statistician, the book applies the methods to real data examples from chemistry. It also examines results of the different methods, comparing traditional approaches with their robust counterparts. The authors use the freely available R package to implement methods.