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Evolving factor analysis in the presence of heteroscedastic noise

✍ Scribed by H.R. Keller; D.L. Massart; Y.Z. Liang; O.M. Kvalheim

Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
577 KB
Volume
263
Category
Article
ISSN
0003-2670

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✦ Synopsis

Evohng factor analysis (EFA) IS a promwng method for the analysis of multlvarlate data with an mtrmstc order When applymg EFA for assessment of peak homogeneity m hqmd chromatography, one has to be aware of mstrumental and expelvnental d8ficulttes Heteroscedastlclty 1s one of the most serious problems and leads to additional etgenvalues that may be mlsmterpreted as bemg due to an lmpunty After appropnate data pretreatment, the fiid-size wmdow EFA technique proved successful for peak punty control m hqmd chromatography with photodlode-array detectlon Less than 1% of a spectrally slmdar lmpunty could be detected for R, values as low as 03

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✍ Christian Ritter; Jean A. Gilliard; Jean Cumps; Bernard Tilquin πŸ“‚ Article πŸ“… 1996 πŸ› Elsevier Science 🌐 English βš– 900 KB

## Window evolving factor analysis (WEFA) is a powerful technique for checking peak purity in liquid chromatography with diode array detection (LC-DAD). However, practical application of the technique can be limited by instrumental and experimental non-idealities. One of the problem sources is het