Recent Submissions

  • Topics in Graph Clustering 

    Wan, Yali
    In this thesis, two problems in social networks will be studied. In the first part of the thesis, we focus on community recovery problems for social networks. There have been many recent theoretical advances in the model-based ...
  • Scalable Manifold Learning and Related Topics 

    McQueen, James
    The subject of manifold learning is vast and still largely unexplored. As a subset of unsupervised learning it has a fundamental challenge in adequately defining the problem but whose solution is to an increasingly important ...
  • Applications of Robust Statistical Methods in Quantitative Finance 

    Green, Christopher George
    Financial asset returns and fundamental factor exposure data often contain outliers, observations that are inconsistent with the majority of the data. Both academic finance researchers and quantitative finance professionals ...
  • Scalable Methods for the Inference of Identity by Descent 

    Grimson, Fiona
    Identity by descent (IBD) describes the shared inheritance of DNA and underlies genetic similarity between individuals. Estimated IBD graphs describing the IBD relationships among individuals have many uses in statistical ...
  • Projection and Estimation of International Migration 

    Azose, Jonathan Jerome
    I propose techniques for improving both estimation and projection of international migration. By applying a Bayesian hierarchical modeling approach to net migration data, I produce projections of international migration ...
  • Bayesian Methods for Inferring Gene Regulatory Networks 

    Young, William Chad
    The recent explosion in the availability of gene expression data has opened up new possibilities in advancing our understanding of the fundamental processes of life. To keep up with the increasing size of the datasets, new ...
  • Finite Sampling Exponential Bounds 

    Greene, Evan
    This dissertation develops new exponential bounds for the tail of the hypergeometric distribution. It is organized as follows. In Chapter 1, it reviews existing exponential bounds used to control the hypergeometric tail. ...
  • Finite Population Inference for Causal Parameters 

    Loh, Wen Wei
    Randomized experiments are often employed to determine whether a treatment X has a causal effect on an outcome Y. Under the Neyman-Rubin causal model with binary X and Y, each patient is characterized by two binary potential ...
  • Likelihood-Based Inference for Partially Observed Multi-Type Markov Branching Processes 

    Xu, Jason
    Markov branching processes are a class of continuous-time Markov chains (CTMCs) frequently used in stochastic modeling with ubiquitous applications. Bivariate or multi-type processes are necessary to model phenomena such ...
  • Space-Time Smoothing Models for Surveillance and Complex Survey Data 

    Mercer, Laina D.
    Area and time-specific estimates of disease rates, cause-specific mortality rates and other key health indicators are of great interest for health care and policy purposes. Such estimates provide the information needed to ...
  • Testing Independence in High Dimensions & Identifiability of Graphical Models 

    Leung, Dennis
    In this thesis two problems in multivariate statistics will be studied. In the first chaper, we treat the problem of testing independence between m continuous observations when m can be larger than the available sample ...
  • Statistical Hurdle Models for Single Cell Gene Expression: Differential Expression and Graphical Modeling 

    McDavid, Andrew
    This dissertation describes a set of statistical methods developed for analysis of single cell gene expression. A characteristic of single cell expression is bimodal expression, in which two clusters of expression are ...
  • Bayesian Modeling of a High Resolution Housing Price Index 

    Ren, You
    Understanding how housing values evolve over time is important to consumers, real estate professionals, and policy makers. Existing methods for constructing housing indices are computed at a coarse spatial granularity, ...
  • Phylogenetic Stochastic Mapping 

    Irvahn, Jan
    Phylogenetic stochastic mapping is a method for reconstructing the history of trait changes on a phylogenetic tree relating species/organisms carrying the trait. State-of-the-art methods assume that the trait evolves ...
  • Degeneracy, Duration, and Co-evolution: Extending Exponential Random Graph Models (ERGM) for Social Network Analysis 

    Li, Ke
    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 

    Theobald, Roderick Jenkins
    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 

    Harmon, James Warren
    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 

    Gerard, David C.
    We present novel methods and new theory in the statistical analysis of tensor-valued data. A tensor is a multidimensional array. When data come in the form of a tensor, special methods and models are required to capture ...
  • Discrete-Time Threshold Regression for Survival Data with Time-Dependent Covariates 

    Sharkansky, Stefan
    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 ...
  • R-squared inference under non-normal error 

    Xu, Lei
    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 ...

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