سال انتشار: ۱۳۷۹

محل انتشار: پنجمین کنفرانس آمار ایران

تعداد صفحات: ۱۷

نویسنده(ها):

Thomas A. Mazzuchi – School of Engineering and Applied Science, The George Washington University, Washington D.C. 20052
Ehsan S. Soofi – Scool of Business Administration, University of Wiscoonsin-Milwaukee, P.O. Box 742, Milwaukee, WI 53201
Refilk Soyer – Department of Management Science, The George Washington University, Washington D.C. 20052
Joseph J. Retzer – Maritz Marketing Resear Inc., 1415 W. 22nd Street, Suite 800, Oak Brook, IL 60523, USA

چکیده:

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.