论文信息 - Estimation for an adaptive allocation design

Estimation for an adaptive allocation design

Abstract The generalized Polya urn model has been proposed as a class of adaptive allocation rules. Under a simple population model, maximum likelihood estimators can be derived. Previous work has shown them to be jointly asymptotically normal. We prove some additional results, including strong consistency of the estimators and a law of the iterated logarithm. We then derive the exact Fisher's information matrix and construct fixed-size confidence regions for a fully sequential procedure.

William F. Rosenberger | T. N. Sriram | W. Rosenberger

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