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National Repository of Grey Literature 3 records found  Search took 0.00 seconds. 
Empirical Estimates in Stochastic Optimization: Special cases
 Kaňková, Vlasta
Classical optimization problems depending on a probability measure belong mostly to nonlinear deterministic optimization problems that are relatively complicated. On the other hand, these problems fulfil very often "suitable" mathematical properties guaranteing the stability (w.r.t. probability measure) and, moreover, giving a possibility to replace the "underlying" probability measure by an empirical one to obtain "good" stochastic estimates of the optimal value and the optimal solution. Properties of thess estimates have been investigated mostly for standard types of probability measures with suitable (thin) tails and independent random samples. However distributions with heavy tails correspond to many economic problems and, moreover, many applications do not correspond to the "classical" problems. The aim of the paper is, first, to try to recall stability results including also heavy tails and more general problems.
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Ekonomické procesy a empirická data
 Kaňková, Vlasta
Optimizatiom problems depending on a completely unknown probability measure are considered. In particular, there are considered optimization problems with objective functions in a form mathematical expectation of functions depednding on a random parameter. In such situations, usually, an empirical measure replaced the theoretical one. The aim of the paper is to discuss corresponding estimates of the optimal value and optimal solution based on the independent as well as on some types od dependent data.
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A Note on Quantitative Stability and Empirical Estimates in Stochastic Programming
 Kaňková, Vlasta ; Houda, M.
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