Regression

Frank Westad, Marta Bevilacqua, Federico Marini

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

29 Citations (Scopus)

Abstract

In this chapter, a survey of the theory behind the main chemometric methods used for multivariate calibration is presented. Ordinary least squares, multiple linear regression, principal component regression, partial least squares regression and principal covariate regression are discussed in detail. Tools for model diagnostics and model interpretation are presented, together with strategies for variable selection.
Original languageEnglish
Title of host publicationChemometrics in Food Chemistry
EditorsFederico Marini
PublisherElsevier
Publication date2013
Pages127 - 170
Chapter4
ISBN (Print)978-0-444-59528-7
DOIs
Publication statusPublished - 2013
Externally publishedYes
SeriesData Handling in Science and Technology
Volume28
ISSN0922-3487

Keywords

  • Calibration
  • Regression
  • Validation
  • Model diagnostics
  • Latent variables
  • Prediction error
  • Variable selection

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