SCSC2003 Abstract S9909
IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS
IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS
Submitting Author: Prof. Nicholas Nechval
Abstract:
In this paper, for identifying an observable process with one of several simulation models, a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem when covariance matrices of multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters.
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