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On localizing global Pareto solutions in a given convex set

Agnieszka DrwalewskaLesław Gajek — 1999

Applicationes Mathematicae

Sufficient conditions are given for the global Pareto solution of the multicriterial optimization problem to be in a given convex subset of the domain. In the case of maximizing real valued-functions, the conditions are sufficient and necessary without any convexity type assumptions imposed on the function. In the case of linearly scalarized vector-valued functions the conditions are sufficient and necessary provided that both the function is concave and the scalarization is increasing with respect...

Information inequalities for the minimax risk of sequential estimators (with applications)

Lesław GajekB. Mizera-Florczak — 1998

Applicationes Mathematicae

Information inequalities for the minimax risk of sequential estimators are derived in the case where the loss is measured by the squared error of estimation plus a linear functional of the number of observations. The results are applied to construct minimax sequential estimators of: the failure rate in an exponential model with censored data, the expected proportion of uncensored observations in the proportional hazards model, the odds ratio in a binomial distribution and the expectation of exponential...

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