Sign In

Communications of the ACM

Communications of the ACM

A modification of Efroymson's technique for stepwise regression analysis

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

Sign In

Sign in using your ACM Web Account username and password to access premium content if you are an ACM member, Communications subscriber or Digital Library subscriber.

Need Access?

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.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account