Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design
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Standard
Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design. / Rinnan, Åsmund; Munck, Lars.
I: Journal of Chemometrics, Bind 26, Nr. 8-9, 04.2012, s. 487-495.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
Rinnan, Å & Munck, L 2012, 'Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design', Journal of Chemometrics, bind 26, nr. 8-9, s. 487-495. https://doi.org/10.1002/cem.2438
APA
Rinnan, Å., & Munck, L. (2012). Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design. Journal of Chemometrics, 26(8-9), 487-495. https://doi.org/10.1002/cem.2438
Vancouver
Rinnan Å, Munck L. Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design. Journal of Chemometrics. 2012 apr.;26(8-9):487-495. https://doi.org/10.1002/cem.2438
Author
Bibtex
@article{e458c92e2955412981c6307e5ec5d8ba,
title = "Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design",
author = "{\AA}smund Rinnan and Lars Munck",
year = "2012",
month = apr,
doi = "10.1002/cem.2438",
language = "English",
volume = "26",
pages = "487--495",
journal = "Journal of Chemometrics",
issn = "0886-9383",
publisher = "Wiley",
number = "8-9",
}
RIS
TY - JOUR
T1 - Significance of the structure of data in partial least squares regression predictions involving both natural and human experimental design
AU - Rinnan, Åsmund
AU - Munck, Lars
PY - 2012/4
Y1 - 2012/4
U2 - 10.1002/cem.2438
DO - 10.1002/cem.2438
M3 - Journal article
VL - 26
SP - 487
EP - 495
JO - Journal of Chemometrics
JF - Journal of Chemometrics
SN - 0886-9383
IS - 8-9
ER -
ID: 40628274