Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    ISSN: 0886-9383
    Keywords: Variable selection ; PLS ; Calibration ; Modelling ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A modified PLS algorithm is introduced with the goal of achieving improved prediction ability. The method, denoted IVS-PLS, is based on dimension-wise selective reweighting of single elements in the PLS weight vector w. Cross-validation, a criterion for the estimation of predictive quality, is used for guiding the selection procedure in the modelling stage. A threshold that controls the size of the selected values in w is put inside a cross-validation loop. This loop is repeated for each dimension and the results are interpreted graphically. The manipulation of w leads to rotation of the classical PLS solution. The results of IVS-PLS are different from simply selecting X-variables prior to modelling. The theory is explained and the algorithm is demonstrated for a simulated data set with 200 variables and 40 objects, representing a typical spectral calibration situation with four analytes. Improvements of up to 70% in external PRESS over the classical PLS algorithm are shown to be possible.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
    Signatur Availability
    BibTip Others were also interested in ...
  • 2
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    Journal of Chemometrics 4 (1990), S. 79-90 
    ISSN: 0886-9383
    Keywords: PLS ; Three-way matrices ; Calibration ; Residual bilinearization ; Background correction ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: When using hyphenated methods in analytical chemistry, the data obtained for each sample are given as a matrix. When a regression equation is set up between an unknown sample (a matrix) and a calibration set (a stack of matrices), the residual is a matrix R.The regression equation is usually solved by minimizing the sum of squares of R. If the sample contains some constituent not calibrated for, this approach is not valid. In this paper an algorithm is presented which partitions R into one matrix of low rank corresponding to the unknown constituents, and one random noise matrix to which the least squares restrictions are applied. Properties and possible applications of the algorithm are also discussed.In Part 2 of this work an example from HPLC with diode array detection is presented and the results are compared with generalized rank annihilation factor analysis (GRAFA).
    Additional Material: 2 Ill.
    Type of Medium: Electronic Resource
    Signatur Availability
    BibTip Others were also interested in ...
  • 3
    ISSN: 0886-9383
    Keywords: PLS ; Three-way matrices ; Calibration ; Residual bilinearization ; Background correction ; GRAFA ; Chemistry ; Analytical Chemistry and Spectroscopy
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The partial least squares-residual bilinearization (PLS-RBL) approach to background correction presented in Part 1 of this work is demonstrated with an example from HPLC with diode array detection. Data are also evaluated with generalized rank annihilation factor analysis (GRAFA) and results are compared.
    Additional Material: 4 Ill.
    Type of Medium: Electronic Resource
    Signatur Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...