Improved estimation and prediction for computationally expensive ecological and paleoclimate models
Date
2016
Authors
Tipton, John, author
Hooten, Mevin, advisor
Opsomer, Jean, advisor
Hoeting, Jennifer, committee member
Aldridge, Cameron, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
In this dissertation, we present statistical methods to evaluate estimation and prediction performance for applied ecological problems. We explore a variety of applied problems and, within this context, we investigate how each method performs. We evaluate empirical performance of a model-based estimator of mean percent canopy cover using a representative United States Forest Service Forest Inventory and Analysis dataset. For two paleoclimate reconstructions, we develop novel modeling methodologies and evaluate model performance using both resampling and simulation methods. In each application, we use proper scoring rules while leveraging parallel computing and computational techniques, that allow fitting of complex models in a finite amount of time.