TY - GEN
T1 - Statistical inference equivalence principle and its applications
AU - Nechval, Nicholas A.
AU - Nechval, Konstantin N.
AU - Rozevskis, Uldis
PY - 2005
Y1 - 2005
N2 - In this paper, we propose a new approach to solve constrained optimization problems under parameter uncertainty. This approach is based on the statistical inference equivalence principle, the idea of which belongs to the authors. It is especially effective when we deal with asymmetric loss functions and small data samples. The results obtained in this paper agree with the simulation results, which confirm the validity of the theoretical predictions of performance of the suggested approach.
AB - In this paper, we propose a new approach to solve constrained optimization problems under parameter uncertainty. This approach is based on the statistical inference equivalence principle, the idea of which belongs to the authors. It is especially effective when we deal with asymmetric loss functions and small data samples. The results obtained in this paper agree with the simulation results, which confirm the validity of the theoretical predictions of performance of the suggested approach.
KW - Constraints
KW - Optimization
KW - Parameter uncertainty
KW - Statistical inference equivalence principle
UR - https://www.scopus.com/pages/publications/84867381507
M3 - Conference paper
AN - SCOPUS:84867381507
SN - 9806560566
SN - 9789806560567
T3 - WMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
SP - 182
EP - 187
BT - WMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
T2 - 9th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2005
Y2 - 10 July 2005 through 13 July 2005
ER -