Thomas A. Mazzuchi - School of Engineering and Applied Science, The George Washington University, Washington D.C. ۲۰۰۵۲
Ehsan S. Soofi - Scool of Business Administration, University of Wiscoonsin-Milwaukee, P.O. Box ۷۴۲, Milwaukee, WI ۵۳۲۰۱
Refilk Soyer - Department of Management Science, The George Washington University, Washington D.C. ۲۰۰۵۲
Joseph J. Retzer - Maritz Marketing Resear Inc., ۱۴۱۵ W. ۲۲nd Street, Suite ۸۰۰, Oak Brook, IL ۶۰۵۲۳, USA

We use the Maximum Entropy Dirichlet (MED) procedure to model consumer choice of long distance provider based on the perceived attributes of the companies. The MED is a computer-intensive method that uses Dirichlet prior and various attribute constraints as inputs and provides maximum entropy models that are in loglinear and logit forms. The MED generates prior and posterior distributions for the parameters of each model and for a Kullback-Leibler information function that measures the fit of the model. The MED also provides posterior distribution for inference about a normalized Kullback-Leibler information index of fit.

Contingency tables, Kullback-Leibler information, Logit, Logistic regression, Loglinear, Noninformative prior.