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Statistické metody pro regresní modely s chybějícími daty / Statistical Methods for Regression Models With Missing Data

The aim of this thesis is to describe and further develop estimation strategies for data obtained by stratified sampling. Estimation of the mean and linear regression model are discussed. The possible inclusion of auxiliary variables in the estimation is exam- ined. The auxiliary variables can be transformed rather than used in their original form. A transformation minimizing the asymptotic variance of the resulting estimator is pro- vided. The estimator using an approach from this thesis is compared to the doubly robust estimator and shown to be asymptotically equivalent.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:382737
Date January 2018
CreatorsNekvinda, Matěj
ContributorsKulich, Michal, Omelka, Marek
Source SetsCzech ETDs
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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