Title
Retro-Regression-Another Important Multivariate Regression Improvement.
Abstract
We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.
Year
DOI
Venue
2001
10.1021/ci000106d
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
Keywords
Field
DocType
multivariate regression
Cross-sectional regression,Multivariate adaptive regression splines,Regression analysis,Regression diagnostic,Polynomial regression,Local regression,Bayesian multivariate linear regression,Statistics,Mathematics,Segmented regression
Journal
Volume
Issue
ISSN
41
3
0095-2338
Citations 
PageRank 
References 
1
0.38
10
Authors
1
Name
Order
Citations
PageRank
Milan Randic1635203.52