0532168 20240103224415.120200915235959.9 2020 Robustní testování hypotéz chyby měření dvouvýběrový test Robust hypothesis testing measurement errors two-sample test cav_un_auth*0263018 Kalina Jan UIVT-O Oddělení strojového učení Department of Machine Learning Department of Machine Learning 34 Ústav informatiky AV ČR, v. v. i. cav_un_auth*0255501 Broniatowski M. FR 33 cav_un_auth*0368969 Jurečková Jana UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics CZ 33 Ústav teorie informace a automatizace AV ČR, v. v. i. https://github.com/jankalinaUI/Likelihood-ratio-testing-under-measurement-errors GA19-05704S GA ČR CZ cav_un_auth*0375756 The implementation in R software performs a robust hypothesis test comparing two samples, which takes into account measurement errors. This is a very unique approach to testing under the presence of measurement errors. The presented code performs a complete analysis, including the computation of the test statistic for a given dataset, the critical value, and evaluates the power of the test. Computing the critical value as well as the power is very tedious but feasible with this software for moderate sample sizes. The software is available under MIT license. BA 10000 10100 10101 2021 3 UTIA-B 10000 10100 10101 UTIA-B BA RVO:67985807 RVO:67985556 http://hdl.handle.net/11104/0310757 cav_un_auth*0296535 Ústav teorie informace a automatizace AV ČR ÚTIA AV ČR CZ cav_un_auth*0324570 Sorbonne Universités FR S 2020 2020