Now showing items 291-300 of 324
Estimation of Change-Points in Spline Models
(2022)
In this dissertation thesis, we present novel, rigorously studied and computationally efficient methods for change-points estimation in different spline models, including linear spline models, generalized linear spline ...
Cell Nuclear Morphology Analysis Using 3D Shape Modeling, Machine Learning and Visual Analytics
(2018)
Quantitative analysis of morphological changes in a cell nucleus is important for the understanding of nuclear architecture and its relationship with cell differentiation, development, proliferation, and disease. Changes ...
On Issues of Scale and Dependence in Spatial and Spatio-Temporal Data
(2019)
Recent years have seen a massive increase in the availability of spatial and spatio-temporal datasets. With these data comes a set of practical challenges, especially when researchers use spatial statistical models to ...
Contributions to Functional Data Analysis and High-Throughput Screening Assay Analysis.
(2012)
Modern science is characterized by complex nature of available data sets. Statisticians are now developing new statistical techniques for analyzing large and complex data sets. This dissertation contributes toward analyzing ...
Genome-wide Approaches to Identifying the Etiologies of Complex Diseases: Applications in Colorectal Cancer and Congenital Heart Disease.
(2013)
Complex diseases have complicated genetic architectures. A more thorough understanding of the genetic contributors to these diseases may offer new insights into the design of prevention and early intervention strategies. ...
The Road to Identifying Disease Causing Genes: Association Tests, Genotype Imputations, and Sampling Strategies for Sequencing Studies.
(2013)
Technological advances now allow investigators to use sequencing data to identify genetic risk variants for complex diseases. However, it is still expensive to sequence a large sample of individuals. While genotype imputation ...
Bayesian Models for Joint Longitudinal and Multi-State Survival Data
(2021)
Biomedical data commonly include repeated measures of biomarkers and disease states over time. When the processes determining the biomarker levels and disease states are related, a joint longitudinal and survival model is ...
Statistical Methods for Large Scale Genetic Analyses
(2021)
Population scale genomic analyses have informed the development of novel therapeutics, diagnostics, and understanding of disease etiology. Among the recent developments in human genetic association analyses, electronic ...
Estimation Methods and Clinical Trial Design in Small n, Sequential, Multiple-Assignment, Randomized Trials
(2021)
The application of a small n, sequential, multiple-assignment randomized trial (snSMART) to rare disease studies remains an active research area. In this dissertation, we present methods that estimate dynamic treatment ...
Joint Mean and Covariance Modeling of Matrix-Variate Data
(2018)
This dissertation addresses theory, methodology, and applications for joint mean and covariance estimation with matrix-variate data. Chapters 2 and 3 consider joint mean and covariance estimation in the Kronecker product ...