Multiway methods

Jose Manuel Amigo Rubio, Federico Marini

11 Citations (Scopus)

Abstract

This chapter provides an overview of the main multiway methods used for data decomposition, calibration and pattern recognition. Parallel factor analysis (PARAFAC), PARAFAC2, Tucker3 and other multiway methods are briefly presented, together with a description and discussion of the main properties and steps of their most popular algorithms. The theoretical explanation is accompanied by some illustrative examples of their application in the field of Food Science (classification of vinegars with Excitation-Emission Fluorescence, ripening of apples measured with GC-MS, sensory analysis and prediction of sugar properties based on fluorescence landscape).

Original languageEnglish
Title of host publicationChemometrics in Food Chemistry
EditorsFederico Marini
Number of pages49
PublisherElsevier
Publication date2013
Pages265-313
Chapter7
ISBN (Print)978-0-444-59528-7
DOIs
Publication statusPublished - 2013
SeriesData Handling in Science and Technology
Volume28
ISSN0922-3487

Fingerprint

Dive into the research topics of 'Multiway methods'. Together they form a unique fingerprint.

Cite this