Accession Number : ADA186043

Title :   Predicting Magazine Audiences with a Loglinear Model.

Descriptive Note : Technical rept.,

Corporate Author : FLORIDA STATE UNIV TALLAHASSEE DEPT OF STATISTICS

Personal Author(s) : Danaher, Peter J

PDF Url : ADA186043

Report Date : Jul 1987

Pagination or Media Count : 28

Abstract : A loglinear model for predicting magazine exposure distributions is developed and its' parameters are estimated by using the maximum likelihood technique. The accuracy of the loglinear and a Dirichlet-multinomial model are compared using 1985 AGB: McNair data. The result show that the loglinear model has significantly smaller prediction errors than the Dirichlet-multinomial model. A simple algorithm for optimal media scheduling is given. Keywords: Advertising; Statistical analysis; Efficiency. (Author)

Descriptors :   *EXPOSURE(GENERAL), *MATHEMATICAL PREDICTION, *MAXIMUM LIKELIHOOD ESTIMATION, ACCURACY, ALGORITHMS, DISTRIBUTION, ERRORS, OPTIMIZATION, SCHEDULING, STATISTICAL ANALYSIS

Subject Categories : Statistics and Probability
      Sociology and Law

Distribution Statement : APPROVED FOR PUBLIC RELEASE