Polynomial multivariate least-squares regression for modeling nonlinear data applied to in-depth characterization of chromatographic resolution

Journal of Chemometrics

Volumn 25, Issue 11, 2011, Pages 575-585

  Vogt, Frank ^a   Gritti, Fabrice ^a   Guiochon, Georges ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

Author keywords

Chromatography; Instrument optimization; Nonlinear calibration models; Polynomial multivariate least squares regression (PMLR); Response surface

Indexed keywords

CALIBRATION; CHROMATOGRAPHY; LEAST SQUARES APPROXIMATIONS; MULTIVARIABLE SYSTEMS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; SURFACE PROPERTIES;

CALIBRATION MODEL; INSTRUMENT OPTIMIZATION; LEAST SQUARES REGRESSION; MULTIVARIATE LEAST SQUARES; NONLINEAR CALIBRATION; NONLINEAR CALIBRATION MODEL; NONLINEAR DATA; OPTIMISATIONS; POLYNOMIAL MULTIVARIATE LEAST-SQUARE REGRESSION; RESPONSE SURFACE;

POLYNOMIALS;

EID: 82255192408     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1403     Document Type: Article

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