A Backward Elimination General Significance Regression Model.
Abstract
The report develops a statistical procedure for selecting a proper set of independent variables in a linear regression model. The procedure is a backward elimination procedure in which initially a large model is hypothesized and systematically non-significant variables are eliminated one by one. Two different situations were investigated concerning sample estimates of the error: pure error, and using lack-of-fit as an error estimate, with the effects on the testing procedure for each case. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1970
- Accession Number
- AD0876630
Entities
People
- Charles E. Colvin
- Maureen E. Machtolff
Organizations
- United States Army Aviation and Missile Command