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


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a186043.pdf


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