@article{943977,
      recid = {943977},
      author = {Wehrens, Ron.},
      title = {Chemometrics with R : Multivariate Data Analysis in the  Natural and Life Sciences /},
      pages = {1 online resource (xvi, 308 pages) :},
      abstract = {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). .},
      url = {http://library.usi.edu/record/943977},
      doi = {https://doi.org/10.1007/978-3-662-62027-4,  https://doi.org/10.1007/978-3-662-62},
}