Spectral mapping, a personal and historical account of an adventure in multivariate data analysis
Spectral mapping is a factorial method of multivariate data analysis that was developed around 1975 in the pharmacological research laboratory of Janssen Pharmaceutica. It has been applied in diverse fields of biology and economics where tabulated data are obtained which are defined on ratio scales....
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Published in | Chemometrics and intelligent laboratory systems Vol. 77; no. 1; pp. 215 - 223 |
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Format | Journal Article |
Language | English |
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Elsevier B.V
28.05.2005
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Abstract | Spectral mapping is a factorial method of multivariate data analysis that was developed around 1975 in the pharmacological research laboratory of Janssen Pharmaceutica. It has been applied in diverse fields of biology and economics where tabulated data are obtained which are defined on ratio scales. The approach has provided a few instances in which useful information was obtained that would be hard to get from bivariate analysis or from “eyeballing” of the raw data. Basically, the approach consists of logarithmic transformation and double centering of the data, factorization of the resulting cross-products matrix and a biplot of the resulting factor scores and loadings. Weighting by the marginal row and column sums of the original data can be applied in order to reduce the leverage of less important row and column items. This paper describes how the approach has fared over the past 30 years from a personal perspective. |
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AbstractList | Spectral mapping is a factorial method of multivariate data analysis that was developed around 1975 in the pharmacological research laboratory of Janssen Pharmaceutica. It has been applied in diverse fields of biology and economics where tabulated data are obtained which are defined on ratio scales. The approach has provided a few instances in which useful information was obtained that would be hard to get from bivariate analysis or from “eyeballing” of the raw data. Basically, the approach consists of logarithmic transformation and double centering of the data, factorization of the resulting cross-products matrix and a biplot of the resulting factor scores and loadings. Weighting by the marginal row and column sums of the original data can be applied in order to reduce the leverage of less important row and column items. This paper describes how the approach has fared over the past 30 years from a personal perspective. |
Author | Lewi, Paul J. |
Author_xml | – sequence: 1 givenname: Paul J. surname: Lewi fullname: Lewi, Paul J. email: plewi@prdebe.jnj.com organization: Center for Molecular Design, Janssen Pharmaceutica, Antwerpsesteenweg 37, B-2350 Vosselaar, Belgium |
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CitedBy_id | crossref_primary_10_1146_annurev_statistics_042720_124436 crossref_primary_10_4236_ajps_2013_411277 crossref_primary_10_3389_fmicb_2021_727398 crossref_primary_10_1214_22_STS880 crossref_primary_10_1007_s11004_018_9754_x |
Cites_doi | 10.1103/PhysRev.76.769 10.2307/1403053 10.1111/j.0006-341X.2003.00130.x 10.1016/0169-7439(94)85039-9 10.1126/science.286.5439.531 10.1111/j.1600-0498.1964.tb00285.x 10.1016/0169-7439(89)80007-3 10.1016/0169-7439(95)80037-A 10.1093/biomet/58.3.453 10.1016/0166-3542(91)90001-8 |
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Keywords | Spectral map analysis Spectral mapping Pharmacology Biplot History Multivariate data analysis |
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Res. doi: 10.1016/0166-3542(91)90001-8 contributor: fullname: Andries – volume: 5 start-page: 44 year: 1984 ident: 10.1016/j.chemolab.2004.07.010_bib27 article-title: Picturing the pharmaceutical environment by Spectramap publication-title: Pharm. Int. contributor: fullname: Lewi – year: 1986 ident: 10.1016/j.chemolab.2004.07.010_bib38 contributor: fullname: Oldroyd – year: 1973 ident: 10.1016/j.chemolab.2004.07.010_bib4 contributor: fullname: Benzécri |
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Title | Spectral mapping, a personal and historical account of an adventure in multivariate data analysis |
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