Global ETD Search

Essays on Model Selection Uncertainty and Model Averaging: Computational and Empirical Work with Beta Regression, Multiple Linear Regression with ARMA Innovations, and the Minimum Description Length Principle

Allenbrand, CorbanUniversity of Kansas2023

Uncertainty in model selection is under-explored and frequently resolved non-rigorously through beliefs about generalizability, practical usefulness, and computational ease. This is problematic as model selection routinely admits multiple models which imposes extra uncertainty on all post-selection …

ku Repository record for Essays on Model Selection Uncertainty and Model Averaging: Computational and Empirical Work with Beta Regression, Multiple Linear Regression with ARMA Innovations, and the Minimum Description Length Principle (opens in a new tab)