Accession Number:

ADA080407

Title:

Cross Validation of Selection of Variables in Multiple Regression.

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1979-12-01

Pagination or Media Count:

128.0

Abstract:

Techniques and criterion for selection of the best subset of variables to be used in a regression model are reviewed. A model was developed using the Automatic Interaction Detection AID algorithm as a pre-screening device for locating those variables most important to the regression including interaction terms. Five previous models including the one developed by AID and one developed by Westinghouse on avionic characteristic data are used in cross validation experiments to determine the predictive power of these models on a new set of data points using the same set of variables. A cross validation R2 value is discussed as a criterion for choosing between competing models. Author

Subject Categories:

  • Aircraft
  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE