RecordNumber
4005
Author
Frank, Ildiko E.
Crop_Body
Ildiko E. Frank, Jerome H. Friedman
Title of Article
A Statistical View of Some Chemometrics Regression Tools
Title Of Journal
TECHNOMETRIC
PublishInfo
American Statistical Association and the American Society for Quality Control
Publication Year
1993
Volum
35
Issue Number
2
Page
109-135
Keywords
Multiple response regression , Partial least squares , Principal components regression , Ridge regression , Variable subset selection
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