Název: Empirical Estimates via Stability in Stochastic Programming
Překlad názvu: Empirické odhady a stabilita ve stochastickém programování
Autoři: Kaňková, Vlasta
Typ dokumentu: Výzkumné zprávy
Rok: 2007
Jazyk: eng
Edice: Research Report, svazek: 2192
Abstrakt: It is known that optimization problems depending on a probability measure correspond to many applications. It is also known that these problems belong mostly to a class of nonlinear optimization problems and, moreover, that very often an ``underlying" probability measure is not completely known. The aim of the research report is to deal with the case when an empirical measure substitutes the theoretical one. In particular, the aim is to generalize reults dealing with convergence rate in the case of empirical esrimates. The introduced results are based on the stability results corresponding to the Wasserstein metric. A relationship berween tails of one-dimensional marginal distribution functions and exponentional rate of convergence are introduced. The corresponding results are focus mainly on ``classical" type of problems corresponding to the cases with penalty and recourse. However, an integer simple recourse case and some special risk funkcionals are discussed also.
Klíčová slova: convergence rate; empirical estimates; integer simple recourse case; problems with penalty and recourse; resk funkcionals; stability; Stochastic programming; Wasserstein metric
Číslo projektu: CEZ:AV0Z10750506 (CEP), GA402/06/1417 (CEP), GA402/05/0115 (CEP), GA402/07/1113 (CEP)
Poskytovatel projektu: GA ČR, GA ČR, GA ČR

Instituce: Ústav teorie informace a automatizace AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný v příslušném ústavu Akademie věd ČR.
Původní záznam: http://hdl.handle.net/11104/0157128

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-38385


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