A unified framework for contrast research of the latent variable multivariate regression methods

Chemometrics and Intelligent Laboratory Systems

Volumn 143, Issue , 2015, Pages 136-145

  He, Zhangming ^a,b   Zhou, Haiyin ^a   Wang, Jiongqi ^a   Zhai, Shouchao ^c  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b UNIVERSITY OF DUISBURG ESSEN   (Germany)

^c TSINGHUA UNIVERSITY   (China)

Author keywords

Calibration and prediction; Canonical correlation regression; Latent variable multivariate regression; Partial least square regression; Principal component regression; Reduced rank regression

Indexed keywords

ARTICLE; CALIBRATION; CANONICAL CORRELATION REGRESSION; CONCEPTUAL FRAMEWORK; CORRELATION COEFFICIENT; ERROR; FAULT DETECTION RATE; LATENT VARIABLE MULTIVARIATE REGRESSION; MEAN SQUARE ERROR; ORDINARY LEAST SQUARE REGRESSION; PARTIAL LEAST SQUARE REGRESSION; PREDICTION; PRINCIPAL COMPONENT REGRESSION; PRIORITY JOURNAL; REDUCED RANK REGRESSION; REGRESSION ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; VALIDATION PROCESS;

EID: 84925349354     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2015.02.006     Document Type: Article

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