Diese Arbeit behandelt zwei Aspekte von Inferenz in Gemischten Modellen. Sie basiert auf Manuskripten, welche im Anhang bereitgestellt sind. Im ersten Teil wird zwischen bedingter und marginaler multipler Inferenz unterschieden und Konfidenzbereiche zum Testen von statistischen Hypothesen hergeleitet. Im zweiten Teil werden Konfidenzbereiche hergeleitet, welche auf dem Lasso beruhen. Diese haben uniforme Bedeckungswahrscheinlichkeiten über dem Raum der Koeffizienten- und Kovarianzparameter.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 confidenc...
This thesis is concerned with the properties of classical estimators of the parameters in mixed lin...
Dissertação apresentada para obtenção do Grau de Doutor em Matemática, Estatística, pela Universidad...
of the bachelor thesis Title: Introduction to Linear Mixed Models Author: Vojtěch Šaroch Department:...
Linear mixed models (LMMs) are suitable for clustered data and are common in biometrics, medicine, s...
Open access financiado por Universite de Geneve (article funding)European Regional Development Fund[...
An approximate Bayesian analysis is considered for data that follow a mixed-effects linear model of ...
AbstractThe paper reviews the linear mixed model with a focus on parameter estimation and inference....
This thesis primarily focuses on the development of statistically valid tools for simultaneous and p...
International audienceA simulation study is performed to investigate the robustness of the maximum l...
This work bridges the frequentist and Bayesian approaches to mixed models by borrowing the best feat...
Today, generalized linear mixed models (GLMM) are broadly used in many fields. However, the developm...
É muito comum encontrar nas áreas agronômica e biológica experimentos cujas observações são correlac...
Mixed linear models are used to analyze data in many settings. These models have in most cases a mul...
Chapter 1 of this dissertation proposes a consistent and locally efficient estimator to estimate the...
This thesis contains three essays on inference in econometric models. Chapter 1 considers the quest...
This thesis is concerned with the properties of classical estimators of the parameters in mixed lin...
Dissertação apresentada para obtenção do Grau de Doutor em Matemática, Estatística, pela Universidad...
of the bachelor thesis Title: Introduction to Linear Mixed Models Author: Vojtěch Šaroch Department:...
Linear mixed models (LMMs) are suitable for clustered data and are common in biometrics, medicine, s...
Open access financiado por Universite de Geneve (article funding)European Regional Development Fund[...
An approximate Bayesian analysis is considered for data that follow a mixed-effects linear model of ...
AbstractThe paper reviews the linear mixed model with a focus on parameter estimation and inference....
This thesis primarily focuses on the development of statistically valid tools for simultaneous and p...
International audienceA simulation study is performed to investigate the robustness of the maximum l...
This work bridges the frequentist and Bayesian approaches to mixed models by borrowing the best feat...
Today, generalized linear mixed models (GLMM) are broadly used in many fields. However, the developm...
É muito comum encontrar nas áreas agronômica e biológica experimentos cujas observações são correlac...
Mixed linear models are used to analyze data in many settings. These models have in most cases a mul...
Chapter 1 of this dissertation proposes a consistent and locally efficient estimator to estimate the...
This thesis contains three essays on inference in econometric models. Chapter 1 considers the quest...
This thesis is concerned with the properties of classical estimators of the parameters in mixed lin...
Dissertação apresentada para obtenção do Grau de Doutor em Matemática, Estatística, pela Universidad...
of the bachelor thesis Title: Introduction to Linear Mixed Models Author: Vojtěch Šaroch Department:...