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RecordNumber
4005
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Author
Frank, Ildiko E.
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Crop_Body
Ildiko E. Frank, Jerome H. Friedman
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Title of Article
A Statistical View of Some Chemometrics Regression Tools
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Title Of Journal
TECHNOMETRIC
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PublishInfo
American Statistical Association and the American Society for Quality Control
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Publication Year
1993
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Volum
35
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Issue Number
2
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Page
109-135
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Keywords
Multiple response regression , Partial least squares , Principal components regression , Ridge regression , Variable subset selection
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Abstract
Chemometrics is a field of chemistry that studies the application of statistical methods to chemical data analysis. In addition to borrowing many techniques from the statistics and engineering literatures, chemometrics itself has given rise to several new data-analytical methods. This article examines two methods commonly used in chemometrics for predictive modeling-partial least squares and principal components regression-from a statistical per- spective. The goal is to try to understand their apparent successes and in what situations they can be expected to work well and to compare them with other statistical methods intended for those situations. These methods include ordinary least squares, variable subset selection, and ridge regression
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