Thesis (Selection of subject)Thesis (Selection of subject)(version: 368)
Thesis details
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Model-based Clustering of Multivariate Longitudinal Data of a Mixed Type
Thesis title in Czech: Modelově založené shlukování vícerozměrných longitudinálních dat smíšeného typu
Thesis title in English: Model-based Clustering of Multivariate Longitudinal Data of a Mixed Type
Key words: modelově založené shlukování|MCMC|longitudinální data|GLMM|smíšený typ
English key words: model-based clustering|MCMC|longitudinal data|GLMM|mixed type
Academic year of topic announcement: 2022/2023
Thesis type: rigorosum thesis
Thesis language: angličtina
Department: Department of Probability and Mathematical Statistics (32-KPMS)
Supervisor: doc. RNDr. Arnošt Komárek, Ph.D.
Author: hidden - assigned and confirmed by the Study Dept.
Date of registration: 17.01.2023
Date of assignment: 17.01.2023
Confirmed by Study dept. on: 17.01.2023
Date and time of defence: 13.02.2023 00:00
Date of electronic submission:17.01.2023
Date of submission of printed version:17.01.2023
Date of proceeded defence: 13.02.2023
Guidelines
Budou vyvinuty Bayesovské přístupy k výběru proměnných v kontextu modelů pro longitudinální data. Budou zkoumány teoretické vlastnosti vyvíjených postupů, které budou též softwarově implementovány.
References
George, E. I. and McCulloch, R. (1997). Approaches for Bayesian variable selection. Statistica Sinica, 7, 339–373.

Griffin, J. E. and Brown, P. J. (2010). Inference with normal-gamma prior distributions in regression problems. Bayesian Analysis, 5, 1339–1349.

Ishwaran, H. and Rao, S. J. (2005). Spike and slab variable selection; frequentist and Bayesian strategies. The Annals of Statistics, 33, 730–773.
 
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