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Degeneracy, Duration, and Coevolution: Extending Exponential Random Graph Models (ERGM) for Social Network Analysis
We address three aspects of statistical methodology in the application of Exponential family Random Graphs to modeling social network processes. The first is the topic of model degeneracy in ERGMs. We show this is a ... 
Lord's Paradox and Targeted Interventions: The Case of Special Education
Lord (1967) describes a hypothetical “paradox” in which two statisticians, analyzing the same dataset using different but defensible methods, come to very different conclusions about the effects of an intervention on student ... 
The Likelihood Pivot: Performing Inference with Confidence
Maximum likelihood estimation is a popular statistical method. To account for possible model misspecification, the sandwich estimate of variance can be used to generate asymptotically correct confidence intervals. Several ... 
Theory and Methods for Tensor Data
We present novel methods and new theory in the statistical analysis of tensorvalued data. A tensor is a multidimensional array. When data come in the form of a tensor, special methods and models are required to capture ... 
DiscreteTime Threshold Regression for Survival Data with TimeDependent Covariates
A natural approach to survival analysis in many settings is to model the subject's ``health'' status as a latent stochastic process, where the terminal event is represented by the first time that the process crosses a ... 
Rsquared inference under nonnormal error
Assessment of the relationship between diet and health status, especially association between diet and chronic disease risk, has attracted lot of research interest in statistical and epidemiologic studies. However, due to ... 
Rsquared inference under nonnormal error
Assessment of the relationship between diet and health status, especially association between diet and chronic disease risk, has attracted lot of research interest in statistical and epidemiologic studies. However, due to ... 
Gravimetric Anomaly Detection using Compressed Sensing
We address the problem of identifying underground anomalies (e.g. holes) based on gravity measurements. This is a theoretically wellstudied yet difficult problem. In all except a few special cases, the inverse problem has ... 
Probabilistic Population Projection for Countries with Generalized HIV/AIDS Epidemics
Population projection has long been an issue for researchers, governments and international organizations so that they can monitor and plan development and resources. The United Nation Population Division (UNPD) publishes ... 
Functional Quantitative Genetics and the Missing Heritability Problem
In classical quantitative genetics, the correlation between the phenotypes of individuals with unknown genotypes and a known pedigree relationship is expressed in terms of probabilities of IBD states. In existing models ... 
Monte Carlo estimation of identity by descent in populations
Genetic similarity between organisms arises from segments of shared genome, which are said to be identical by descent (IBD). Modeling IBD in pedigrees forms the basis of classical linkage analysis and has been a fruitful ... 
Bayesian spatial and temporal methods for public health data
In this thesis, we develop flexible models to analyze public health data in time and/or in space. The development of our methodology is motivated by two examples: cancer incidence data in Washington State and birth outcome ... 
Predictive Modeling of Cholera Outbreaks in Bangladesh
Despite seasonal cholera outbreaks in Bangladesh, little is known about the relationship between environmental conditions and cholera cases. We seek to develop a predictive model for cholera outbreaks in Bangladesh based ... 
Bayesian spatial and temporal methods for public health data
In this thesis, we develop flexible models to analyze public health data in time and/or in space. The development of our methodology is motivated by two examples: cancer incidence data in Washington State and birth outcome ... 
An Algorithmic Framework for High Dimensional Regression with Dependent Variables
(20140224)We present an exploration of the rich theoretical connections between several classes of regularized models, network flows, and recent results in submodular function theory. This work unifies key aspects of these problems ... 
Statistical inference using Kronecker structured covariance
(20131114)We present results for testing and estimation in the context of separable covariance models. We concentrate on two types of data: relational data and crossclassified data. Relational data is frequently represented by a ... 
Modeling Heterogeneity within and between Matrices and Arrays
(20131114)Datasets in the form of matrices and arrays arise frequently in the social and biological sciences and are characterized by measurements indexed by two or more factors. In this dissertation we address two problems relating ... 
ShapeConstrained Inference for ConcaveTransformed Densities and their Modes
(20131114)We consider inference about functions estimated via shape constraints based on concavity. We consider logconcave densities and other “concavetransformed” densities on the real line, where a concavetransformed class is ... 
Estimating Population Size Using the Network Scale Up Method
(20130725)We develop methods for estimating hardtoreach populations from data collected using networkbased questions on standard surveys. Such data arise by asking respondents how many people they know in a specific group (e.g. ... 
Bayesian Nonparametric Inference of Effective Population Size Trajectories from Genomic Data
(20130725)Phylodynamics is an area at the intersection of phylogenetics and population genetics that aims to reconstruct population size trajectories from genetic data. Phylodynamic methods rely on a standard framework based on the ...