Statistical Methods for Modeling the Spatial Structure on the Visual Field in Glaucoma Progression

University of Northern Colorado. Applied Statistics & Research Methods. degree granting institution.

The research presented in this thesis focuses on two alternative statistical methods for spatial

. Many tests of goodness-of-fit are available as evident from the extensive research done; however, those

recalls. This research studies consumer product recall decision making in the automotive industry. The

iterations. Furthermore, this research also realizes the distributed parallelization of the proposed method

parameters as random, rather than fixed. In so doing, Bayesian methods are able to incorporate uncertainty

This research focuses on using statistical learning methods on high-dimensional biological data

proposed estimator are analyzed. The method's validity is established using various goodness-of-fit tests

high school. Previous research has suggested that Job Corps generated a positive average impact in

underlying parameter so that previous work has relied heavily on large sample methods to establish results

competitor to probabilistic inference for unsupervised latent structure learning. We hope our research serves