Essays on Inference in Linear Mixed Models
von Peter Kramlinger
Datum der mündl. Prüfung:2020-04-28
Erschienen:2020-05-11
Betreuer:Prof. Dr. Tatyana Krivobokova
Gutachter:Prof. Dr. Tatyana Krivobokova
Gutachter:Prof. Dr. Stefan Sperlich
Dateien
Name:Dissertation_Kramlinger.pdf
Size:646.Kb
Format:PDF
Zusammenfassung
Englisch
This work addresses two aspects of inference in linear mixed models. It is based on two manuscripts, which are provided as addenda. The first manuscript deals with the distinction between marginal and conditional multiple inference, and provides confidence sets useful for testing in each scenario. The second manuscript is concerned with the issue of constructing confidence sets based on the lasso, which hold uniformly over the space of coefficient and covariance parameters.
Keywords: Small Area Estimation; Marginal Inference; Conditional Inference; Multiple testing; simultaneous inference; Lasso; Sparsity; REML; Variance components