Kim Harry Esbensen
Kim Harry Esbensen
Consultant, professor
Verified email at - Homepage
Cited by
Cited by
Principal component analysis
S Wold, K Esbensen, P Geladi
Chemometrics and intelligent laboratory systems 2 (1-3), 37-52, 1987
Multivariate data analysis: in practice: an introduction to multivariate data analysis and experimental design
KH Esbensen, D Guyot, F Westad, LP Houmoller
Multivariate Data Analysis, 2002
Multi‐way principal components‐and PLS‐analysis
S Wold, P Geladi, K Esbensen, J Öhman
Journal of chemometrics 1 (1), 41-56, 1987
Multivariate data analysis in chemistry
S Wold, C Albano, WJ Dunn, U Edlund, K Esbensen, P Geladi, S Hellberg, ...
Chemometrics, 17-95, 1984
Chemometrics: mathematics and statistics in chemistry
BR Kowalski
Springer Science & Business Media, 2013
Pattern recognition: finding and using regularities in multivariate data
S Wold, C Albano, WJ Dunn III, K Esbensen, S Hellberg, E Johansson, ...
Food research and data analysis 3, 183-185, 1983
Monitoring of anaerobic digestion processes: A review perspective
M Madsen, JB Holm-Nielsen, KH Esbensen
Renewable and sustainable energy reviews 15 (6), 3141-3155, 2011
Multivariate data analysis
KH Esbensen, D Guyot, F Westad
practice 4, 2009
Representative sampling for reliable data analysis: theory of sampling
L Petersen, P Minkkinen, KH Esbensen
Chemometrics and intelligent laboratory systems 77 (1-2), 261-277, 2005
Principal component analysis of multivariate images
P Geladi, H Isaksson, L Lindqvist, S Wold, K Esbensen
Chemometrics and Intelligent Laboratory Systems 5 (3), 209-220, 1989
Principles of proper validation: use and abuse of re‐sampling for validation
KH Esbensen, P Geladi
Journal of Chemometrics 24 (3‐4), 168-187, 2010
Strategy of multivariate image analysis (MIA)
K Esbensen, P Geladi
Chemometrics and Intelligent Laboratory Systems 7 (1-2), 67-86, 1989
Principal component analysis: concept, geometrical interpretation, mathematical background, algorithms, history, practice
KH Esbensen, P Geladi
Elsevier, 2009
Polycyclic aromatic hydrocarbons in soil and air: statistical analysis and classification by the SIMCA method
NB Vogt, F Brakstad, K Thrane, S Nordenson, J Krane, E Aamot, K Kolset, ...
Environmental science & technology 21 (1), 35-44, 1987
Representative mass reduction in sampling—a critical survey of techniques and hardware
L Petersen, CK Dahl, KH Esbensen
Chemometrics and Intelligent Laboratory Systems 74 (1), 95-114, 2004
FTIR spectroscopy for grape and wine analysis
R Bauer, H Nieuwoudt, FF Bauer, J Kossmann, KR Koch, KH Esbensen
Analytical chemistry 80 (5), 1371-1379, 2008
On‐line near infrared monitoring of glycerol‐boosted anaerobic digestion processes: Evaluation of process analytical technologies
JB Holm‐Nielsen, CJ Lomborg, P Oleskowicz‐Popiel, KH Esbensen
Biotechnology and bioengineering 99 (2), 302-313, 2008
Regression on multivariate images: principal component regression for modeling, prediction and visual diagnostic tools
P Geladi, K Esbensen
Journal of Chemometrics 5 (2), 97-111, 1991
An application of calculated fuzzy risk
C Huang
Information Sciences 142 (1-4), 37-56, 2002
Modelling data tables by principal components and PLS: class patterns and quantitative predictive relations
S Wold, C Albano, WJ DUNN III, K Esbensen, S Hellberg
Analusis (Imprimé) 12 (10), 477-485, 1984
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