Stochastic Fatigue Models for Efficient Planning Inspections in Service of Aircraft Structures
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Improved estimation of state of stochastic systems via invariant embedding technique
WSEAS Transactions on Mathematics
Solving operational statistics via a Bayesian analysis
Operations Research Letters
A practical inventory control policy using operational statistics
Operations Research Letters
ASMTA'11 Proceedings of the 18th international conference on Analytical and stochastic modeling techniques and applications
ASMTA'12 Proceedings of the 19th international conference on Analytical and Stochastic Modeling Techniques and Applications
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In the present paper, for improvement or optimization of statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a performance index is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, application examples are given.