1989
DOI: 10.1016/s0021-9673(01)89146-9
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Uniform shell designs for optimization in reversed-phase liquid chromatography

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Cited by 62 publications
(16 citation statements)
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“…and the number of parameters to be estimated from the fitted multiple linear-quadratic regression equation is equal to (d + 1) (d + 2)/2 (Hu and Massart, 1989). In our HS-SPME optimization study, there are a total of 4 2 + (4 + 1) = 21 + 3 center point replicates = 24 points in the complete Doehlert design and (4 + 1) (4 + 2)/2 = 15 parameters to be estimated from multiple linearquadratic regression, as expressed in the following equation:…”
Section: Doehlert Optimizationmentioning
confidence: 99%
“…and the number of parameters to be estimated from the fitted multiple linear-quadratic regression equation is equal to (d + 1) (d + 2)/2 (Hu and Massart, 1989). In our HS-SPME optimization study, there are a total of 4 2 + (4 + 1) = 21 + 3 center point replicates = 24 points in the complete Doehlert design and (4 + 1) (4 + 2)/2 = 15 parameters to be estimated from multiple linearquadratic regression, as expressed in the following equation:…”
Section: Doehlert Optimizationmentioning
confidence: 99%
“…The main advantages of the use of multivariate methods are the necessity of fewer experiments, reducing cost and time, and the possibility to obtain information about interaction between variables, which is not possible in univariate optimization. Most popular multivariate strategies are based on response surface methodology (RSM), which is a multivariate technique that fits, mathematically, the experimental domain in the theoretical design by use of a response function [28,29]. In this field, second-order designs like Central Composite, Box-Behnken or Doehlert matrix have been employed to establish the mathematical relationship (model) among factors (experimental variables in the levels tested) and experimental response [30].…”
Section: Introductionmentioning
confidence: 99%
“…They need fewer experiments, which are more efficient and can moved through the experimental field, and points obtained from a previous design could be used in later designs when they are adjacent [15]. In addition, the quantity of the levels related to each factor can be selected in order to obtain more information about significant or problematic factors [16].…”
Section: Introductionmentioning
confidence: 99%