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Analysis of Biosensoric Data
Timková, Jana ; Hlávka, Zdeněk (advisor) ; Antoch, Jaromír (referee)
Mioijnqt.rjsip IIOKSIOJ ' jjiijjsmnmqotq oqj j mopinu 's ^.loAvmiu.ij sppom p.ixiin 'riiiisu ini' |HUI? HI si >[.TOA\i jo TI.IO.IUO.) oqj '^Hrilll.Il^l r)Af>[AU[l[ .'S'.v,>.If)/) 1) jtllltl-J b\l )(l^(j I^^ HUI![' :.!.() If {ll.y ^,)],) iuiAupf)i[ui[ s iq,)poin ()q V. l}SOMIUOJI.ld HI! ]lST)|StAir/ A "CI"T ItI '1?> :ni,p.)f'n\[
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Bayesian and Maximum Likelihood Nonparametric Estimation in Monotone Aalen Model
Timková, Jana ; Volf, Petr (advisor) ; Kraus, David (referee) ; Komárek, Arnošt (referee)
This work is devoted to seeking methods for analysis of survival data with the Aalen model under special circumstances. We supposed, that all regression functions and all covariates of the observed individuals were nonnegative and we named this class of models monotone Aalen models. To find estimators of the unknown regres- sion functions we considered three maximum likelihood based approaches, namely the nonparametric maximum likelihood method, the Bayesian analysis using Beta processes as the priors for the unknown cumulative regression functions and the Bayesian analysis using a correlated prior approach, where the regression functions were supposed to be jump processes with a martingale structure.
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Bayesian and Maximum Likelihood Nonparametric Estimation in Monotone Aalen Model
Timková, Jana
This work is devoted to seeking methods for analysis of survival data with the Aalen model under special circumstances. We supposed, that all regres- sion functions and all covariates of the observed individuals were nonnegative and we named this class of models monotone Aalen models. To find estimators of the unknown regression functions we considered three maximum likelihood based approaches, namely the nonparametric maximum likelihood method, the Bayesian analysis using Beta processes as the priors for the unknown cumulative regression functions and the Bayesian analysis using a correlated prior approach, where the regression functions were supposed to be jump processes with a martingale structure. Powered by TCPDF (www.tcpdf.org)
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Bayesian and Maximum Likelihood Nonparametric Estimation in Monotone Aalen Model
Timková, Jana ; Volf, Petr (advisor) ; Kraus, David (referee) ; Komárek, Arnošt (referee)
This work is devoted to seeking methods for analysis of survival data with the Aalen model under special circumstances. We supposed, that all regression functions and all covariates of the observed individuals were nonnegative and we named this class of models monotone Aalen models. To find estimators of the unknown regres- sion functions we considered three maximum likelihood based approaches, namely the nonparametric maximum likelihood method, the Bayesian analysis using Beta processes as the priors for the unknown cumulative regression functions and the Bayesian analysis using a correlated prior approach, where the regression functions were supposed to be jump processes with a martingale structure.
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Bayesian and Maximum Likelihood Nonparametric Estimation in Monotone Aalen Model
Timková, Jana
This work is devoted to seeking methods for analysis of survival data with the Aalen model under special circumstances. We supposed, that all regres- sion functions and all covariates of the observed individuals were nonnegative and we named this class of models monotone Aalen models. To find estimators of the unknown regression functions we considered three maximum likelihood based approaches, namely the nonparametric maximum likelihood method, the Bayesian analysis using Beta processes as the priors for the unknown cumulative regression functions and the Bayesian analysis using a correlated prior approach, where the regression functions were supposed to be jump processes with a martingale structure. Powered by TCPDF (www.tcpdf.org)
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Analysis of Biosensoric Data
Timková, Jana ; Antoch, Jaromír (referee) ; Hlávka, Zdeněk (advisor)
Mioijnqt.rjsip IIOKSIOJ ' jjiijjsmnmqotq oqj j mopinu 's ^.loAvmiu.ij sppom p.ixiin 'riiiisu ini' |HUI? HI si >[.TOA\i jo TI.IO.IUO.) oqj '^Hrilll.Il^l r)Af>[AU[l[ .'S'.v,>.If)/) 1) jtllltl-J b\l )(l^(j I^^ HUI![' :.!.() If {ll.y ^,)],) iuiAupf)i[ui[ s iq,)poin ()q V. l}SOMIUOJI.ld HI! ]lST)|StAir/ A "CI"T ItI '1?> :ni,p.)f'n\[
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Testování homogenity a dobré shody v analýze přežití
Timková, Jana
The present paper deals with the goodness of fit and the twosample problem related to the event-history type data. The proposed methods are derived from bayesian nonparametric approach and take advantage of MCMC estimation of the hazard rate. The technique is based on Bayes construction of martingale residuals.
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