Tipton, John, authorHooten, Mevin, advisorOpsomer, Jean, advisorHoeting, Jennifer, committee memberAldridge, Cameron, committee member2016-07-122018-07-112016http://hdl.handle.net/10217/173373In 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.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Improved estimation and prediction for computationally expensive ecological and paleoclimate modelsText