The computational technique conventionally used for stepwise multiple linear regression requires the storage of an n × n matrix of data. When the number of variables, n, is large, this requirement taxes the storage capacity of presently used machinery. The near symmetry of the matrices involved permits a modification requiring only half the storage and computations of the conventional algorithm and this additional storage allows the analysis of problems containing more variables. Alternatively, it permits the analysis of problems containing the same number of variables but with all computations performed in double precision.
The full text of this article is premium content
No entries found
Log in to Read the Full Article
Please select one of the options below for access to premium content and features.
Create a Web Account
If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.
Join the ACM
Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.
Subscribe to Communications of the ACM Magazine
Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.
Purchase the Article
Non-members can purchase this article or a copy of the magazine in which it appears.