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Original title:
Empirical Estimates in Stochastic Optimization: Special cases
Authors: Kaňková, Vlasta
Document type: Papers
Conference/Event: Výpočtová ekonomie, 4. seminář, Plzeň (CZ), 2008-12-18
Year: 2010
Language: eng
Abstract: 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.
Keywords: convergence rate; empirical estimates; exponential tails; heavy tails; L_1 norm; Lipschitz property; Pareto distribution; risk functional; stochastic programming problems
Project no.: CEZ:AV0Z10750506 (CEP), GAP402/10/0956 (CEP), GA402/07/1113 (CEP), GA402/08/0107 (CEP), GA402/06/0990 (CEP)
Funding provider: GA ČR, GA ČR, GA ČR, GA ČR
Host item entry: Výpočtová ekonomie, sborník 4.semináře, ISBN 978-80-7043-773-5
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2011/E/kankova-empirical estimates in stochastic optimization special cases.pdf
Original record: http://hdl.handle.net/11104/0196952
Permalink: http://www.nusl.cz/ntk/nusl-42763
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Authors: Kaňková, Vlasta
Document type: Papers
Conference/Event: Výpočtová ekonomie, 4. seminář, Plzeň (CZ), 2008-12-18
Year: 2010
Language: eng
Abstract: 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.
Keywords: convergence rate; empirical estimates; exponential tails; heavy tails; L_1 norm; Lipschitz property; Pareto distribution; risk functional; stochastic programming problems
Project no.: CEZ:AV0Z10750506 (CEP), GAP402/10/0956 (CEP), GA402/07/1113 (CEP), GA402/08/0107 (CEP), GA402/06/0990 (CEP)
Funding provider: GA ČR, GA ČR, GA ČR, GA ČR
Host item entry: Výpočtová ekonomie, sborník 4.semináře, ISBN 978-80-7043-773-5
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2011/E/kankova-empirical estimates in stochastic optimization special cases.pdf
Original record: http://hdl.handle.net/11104/0196952
Permalink: http://www.nusl.cz/ntk/nusl-42763
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Record created 2011-07-04, last modified 2024-01-26