The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON MATHEMATICS
Transactions ID Number: 31-780
Full Name: Nicholas Nechval
Position: Professor
Age: ON
Sex: Male
Address: University of Latvia, Dept. of Mathematical Statistics, Raina Blvd 19, LV-1050, Riga
Country: LATVIA
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E-mail address: nechval@junik.lv
Other E-mails: konstan@tsi.lv
Title of the Paper: Statistical Validation of Simulation Models of Observable Processes and its Applications
Authors as they appear in the Paper: Nicholas Nechval, Gundars Berzins, Maris Purgailis, Konstantin Nechval
Email addresses of all the authors: nechval@junik.lv,,konstan@tsi.lv
Number of paper pages: 12
Abstract: In this paper, for statistical validation of simulation models of observable processes, 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. The examples of applications are given. We develop also some non-Bayesian exact solutions based on pivotal quantities. The pivotal quantities we have developed are functions of the sufficient statistics. The use of the pivotal quantities is discussed and illustrated via Hotelling's two-sample T2 test in testing the validity of a multivariate stationary response simulation model.
Keywords: Observable process; Simulation model; Validation; GMLR statistic; Pivotal quantity
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