0532129 20250123092555.820200914235959.9 000668460800097 7 s. E cav_un_epca*0532128978-80-7509-734-7636-642BrnoMendel University in Brno2020KapounekSvatoplukVránováHana bivariate geometric distribution competing risks unemployment data 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/2020/SI/volf-0532129.pdf GA18-02739S GA ČR cav_un_auth*0363963 The contribution studies the statistical model for discrete time two-variate duration (time-to-event) data. The analysis is complicated by partial data observation caused either by the right-side censoring or by the presence of dependent competing events. The case is modeled and analyzed with the aid of a two-variate geometric distribution. The model identifiability is discussed and it is shown that the model is not identifiable without proper additional assumptions. The method of analysis is illustrated both on artificially generated example and on real unemployment data. cav_un_auth*0395560 INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2020) /38./ 20200909 20200911 Brno CZ BB 10000 10100 10103 2021 1 PR RVO:67985556 http://hdl.handle.net/11104/0310739 S 2020 C SCOPUS PUBMED 000668460800097 WOS cav_un_epca*0532128 38th INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2020) : Conference Proceedings 978-80-7509-734-7 636 642 Brno Mendel University in Brno 2020 340 Kapounek Svatopluk 340 Vránová Hana