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Statistical Identification of Multinomial populations with sequential sampling
by
Hokwon A. Cho
University of Nevada, Las Vegas
We study the statistical identification in multinomial models using inverse-type sequential procedures. Based on the criteria of likelihood ratios, a stopping rule is devised that controls the probability of a correct identification, PCI and satisfies a preassigned condition P*. Numerical results of the proposed procedure are presented for illustration by performing Monte Carlo experiment.
Date received: October 26, 2005
Copyright © 2005 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # carr-16.