A review of variable selection methods in partial least squares regression T Mehmood, KH Liland, L Snipen, S Sæbø Chemometrics and intelligent laboratory systems 118, 62-69, 2012 | 1589 | 2012 |
pls: Partial Least Squares and Principal Component regression, R package KH Liland, BH Mevik, R Wehrens, P Hiemstra https://cran.r-project.org/package=pls, 2021 | 808* | 2021 |
Optimal choice of baseline correction for multivariate calibration of spectra KH Liland, T Almøy, BH Mevik Applied spectroscopy 64 (9), 1007-1016, 2010 | 299 | 2010 |
Multivariate methods in metabolomics–from pre-processing to dimension reduction and statistical analysis KH Liland TrAC Trends in Analytical Chemistry 30 (6), 827-841, 2011 | 288 | 2011 |
micropan: an R-package for microbial pan-genomics L Snipen, KH Liland BMC bioinformatics 16, 1-8, 2015 | 186 | 2015 |
Comparison of the digestion of caseins and whey proteins in equine, bovine, caprine and human milks by human gastrointestinal enzymes RA Inglingstad, TG Devold, EK Eriksen, H Holm, M Jacobsen, KH Liland, ... Dairy science & technology 90 (5), 549-563, 2010 | 184 | 2010 |
Comparison of variable selection methods in partial least squares regression T Mehmood, S Sæbø, KH Liland Journal of Chemometrics 34 (6), e3226, 2020 | 133 | 2020 |
Model‐based pre‐processing in Raman spectroscopy of biological samples KH Liland, A Kohler, NK Afseth Journal of Raman Spectroscopy 47 (6), 643-650, 2016 | 129 | 2016 |
Canonical partial least squares—a unified PLS approach to classification and regression problems UG Indahl, KH Liland, T Næs Journal of Chemometrics: A Journal of the Chemometrics Society 23 (9), 495-504, 2009 | 123 | 2009 |
Baseline: baseline correction of spectra KH Liland, BH Mevik, R Canteri R package version 1, 2-1, 2015 | 67* | 2015 |
Feasibility of NIR interactance hyperspectral imaging for on-line measurement of crude composition in vacuum packed dry-cured ham slices P Gou, E Santos-Garcés, M Høy, JP Wold, KH Liland, E Fulladosa Meat science 95 (2), 250-255, 2013 | 67 | 2013 |
Pls: partial least squares and principal component regression. R package version 2.8-0 KH Liland, BH Mevik, R Wehrens, P Hiemstra The Comprehensive R Archive Network, 2021 | 57 | 2021 |
Variable selection in multi-block regression A Biancolillo, KH Liland, I Måge, T Næs, R Bro Chemometrics and Intelligent Laboratory Systems 156, 89-101, 2016 | 57 | 2016 |
Co-fermentation Involving Saccharomyces cerevisiae and Lactobacillus Species Tolerant to Brewing-Related Stress Factors for Controlled and Rapid Production … A Dysvik, SL La Rosa, KH Liland, KS Myhrer, HM Østlie, G De Rouck, ... Frontiers in microbiology 11, 279, 2020 | 56 | 2020 |
Determination of O2 and CO2 transmission rate of whole packages and single perforations in micro-perforated packages for fruit and vegetables H Larsen, KH Liland Journal of Food Engineering 119 (2), 271-276, 2013 | 48 | 2013 |
Comparison of UV-C and pulsed UV light treatments for reduction of Salmonella, Listeria monocytogenes, and enterohemorrhagic Escherichia coli on eggs AL Holck, KH Liland, SM Drømtorp, M Carlehög, A McLeod Journal of food protection 81 (1), 6-16, 2018 | 47 | 2018 |
The use of Fourier‐transform infrared spectroscopy to characterize connective tissue components in skeletal muscle of Atlantic cod (Gadus morhua L.) KW Sanden, A Kohler, NK Afseth, U Böcker, SB Rønning, KH Liland, ... Journal of Biophotonics 12 (9), e201800436, 2019 | 46 | 2019 |
Powered partial least squares discriminant analysis KH Liland, UG Indahl Journal of Chemometrics: A Journal of the Chemometrics Society 23 (1), 7-18, 2009 | 45 | 2009 |
Customized baseline correction KH Liland, EO Rukke, EF Olsen, T Isaksson Chemometrics and Intelligent Laboratory Systems 109 (1), 51-56, 2011 | 43 | 2011 |
FTIR-based hierarchical modeling for prediction of average molecular weights of protein hydrolysates KA Kristoffersen, KH Liland, U Böcker, SG Wubshet, D Lindberg, SJ Horn, ... Talanta 205, 120084, 2019 | 42 | 2019 |