bibtype	J - Journal Article
ARLID	0346165
utime	20240903170621.7
mtime	20100914235959.9
WOS	000280425000011
title (primary) (eng)	Empirical Estimates in Stochastic Optimization via Distribution Tails
specification	page_count 13 s.
serial	ARLID cav_un_epca*0297163 ISSN 0023-5954 title Kybernetika volume_id 46 volume 3 (2010) page_num 459-471 publisher name Ústav teorie informace a automatizace AV ČR, v. v. i.
keyword	Stochastic programming problems
keyword	Stability
keyword	Wasserstein metric
keyword	L_1 norm
keyword	Lipschitz property
keyword	Empirical estimates
keyword	Convergence rate
keyword	Exponential tails
keyword	Heavy tails
keyword	Pareto distribution
keyword	Risk functional
keyword	Empirical quantiles
author (primary)	ARLID cav_un_auth*0101122 name1 Kaňková name2 Vlasta full_dept (cz) Ekonometrie full_dept (eng) Department of Econometrics department (cz) E department (eng) E institution UTIA-B full_dept Department of Econometrics garant G fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source	url http:library.utia.cas.cz/separaty/2010/E/kankova-empirical estimates in stochastic optimization via distribution tails.pdf
cas_special	project project_id GA402/07/1113 agency GA ČR ARLID cav_un_auth*0228801 project project_id GA402/08/0107 agency GA ČR country CZ ARLID cav_un_auth*0240545 project project_id LC06075 agency GA MŠk country CZ ARLID cav_un_auth*0227048 research CEZ:AV0Z10750506 abstract (eng) Classical optimization problems depending on a probability measure belong mostly to nonlinear deterministic problems that are, from the numerical point of view, relatively complicated. On the other hand, these problems fulfil very often assumptions giving a possibility to replace the ``underlying" probability measure by an empirical one to obtain ``good" empirical estimates of the optimal value and the optimal solution. Convergence rate of these estimates have been studied mostly for ``underlying" probability measure with suitable (thin) tails. However it is known that probability distributions with heavy tails better correspond to many economic problems. The paper focus on distributions with finite first moments and heavy tails. The introduced assertions are based on the stability results corresponding to the Wasserstein metric with an ``underlying" l_1 norm and empirical quantiles convergence. action ARLID cav_un_auth*0263053 name International Conference on Mathematical Methods in Economy and Industry place České Budějovice dates 15.06.2009-18.06.2009 country CZ reportyear 2011 RIV BB mrcbC52 4 O 4o 20231122134115.4 permalink http://hdl.handle.net/11104/0187260 mrcbT16-e COMPUTERSCIENCECYBERNETICS mrcbT16-f 0.562 mrcbT16-g 0.219 mrcbT16-h 8.1 mrcbT16-i 0.00125 mrcbT16-j 0.22 mrcbT16-k 463 mrcbT16-l 73 mrcbT16-q 21 mrcbT16-s 0.323 mrcbT16-y 20.57 mrcbT16-x 0.48 mrcbT16-4 Q2 mrcbT16-B 27.15 mrcbT16-C 23.684 mrcbT16-D Q3 mrcbT16-E Q2 arlyear 2010 mrcbTft \nSoubory v repozitáři: 0346165.pdf mrcbU34 000280425000011 WOS mrcbU63 cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 46 č. 3 2010 459 471 Ústav teorie informace a automatizace AV ČR, v. v. i.