0561011 20230316105507.120220912235959.9 8 s. P cav_un_epca*0561010978-80-88064-62-6398-404JihlavaCollege of Polytechnics Jihlava2022VojáčkováHana stochastic optimization regression model statistical estimation cav_un_auth*0101227 Volf Petr UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics 100 Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2022/SI/volf-0561011.pdf GA18-02739S GA ČR cav_un_auth*0363963 In the contribution we study consequences of imperfect information to precision of stochastic optimization solution. In particular, it is assumed that the characteristics of optimization problem are influenced by a set of covariates. This dependence is described via a regression model. Hence, the uncertainty is then caused by statistical estimation of regression parameters. The contribution will analyze several regression model cases, together with their application. Precision of results will be explored, both theoretically as well as with the aid of simulations. cav_un_auth*0436095 International Conference Mathematical Methods in Economics 2022 /40./ 20220907 Jihlava CZ 20220909 BB 10000 10100 10103 2023 1 PR RVO:67985556 https://hdl.handle.net/11104/0333905 S 2022 K SCOPUS PUBMED WOS cav_un_epca*0561010 Proceedingsof the 40th International Conference Mathematical Methods in Economics 2022 College of Polytechnics Jihlava 2022 Jihlava 398 404 978-80-88064-62-6 Vojáčková Hana 340