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Browsing Statistics by Title
Now showing items 58-77 of 108
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Methods for estimation and inference for high-dimensional models
This thesis tackles three different problems in high-dimensional statistics. The first two parts of the thesis focus on estimation of sparse high-dimensional undirected graphical models under non-standard conditions, ... -
Methods for the Statistical Analysis of Preferences, with Applications to Social Science Data
Preference data, such as rankings and ratings, are prevalent in the social sciences for expressing and measuring attitudes or opinions. Oftentimes, deterministic algorithms or summary statistics are used to aggregate ... -
Methods, Models, and Interpretations for Spatial-Temporal Public Health Applications
Improving the health of communities and individuals around the world is one of the great challenges of this densely connected global era which finds itself rife with disparity. In order to make the best use of our limited ... -
Metric Learning for Hermitian Manifolds
In recent years, manifold learning has emerged as one of the most promising approaches for performing nonparametric dimension reduction. While numerous manifold learning algorithms of varying degrees of complexity have ... -
Missing Data Methods for Observational Health Dataset
This dissertation is motivated by missing data problems arising from two observational health datasets. The first dataset is created by the SWOG study that linked medicare claims to a prostate cancer prevention trial ... -
Mixture models to fit heavy-tailed, heterogeneous or sparse data
With the advent of modern technologies, many scientific fields collect and analyze increasingly large datasets. Unfortunately, the complexity and heterogeneity of these datasets cannot be properly captured through classical ... -
Model-Based Penalized Regression
This thesis contains three chapters that consider penalized regression from a model-based perspective, interpreting penalties as assumed prior distributions for unknown regression coefficients. In the first chapter, we ... -
Modeling Heterogeneity within and between Matrices and Arrays
(2013-11-14)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 ... -
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 ... -
Monte Carlo likelihood calculation for identity by descent data
(1999)Two individuals are identical by descent at a genetic locus if they share the same gene copy at that locus due to inheritance from a recent common ancestor. Identity by descent can be thought of as a continuous process ... -
Non-Gaussian Graphical Models: Estimation with Score Matching and Causal Discovery under Zero-Inflation
Graphical models specify conditional independence relations between variables. These include undirected graphical models and directed graphical models, the latter of which also capture causal relationships. This dissertation ... -
Nonparametric inference on monotone functions, with applications to observational studies
In this dissertation, we study general strategies for constructing nonparametric monotone function estimators in two broad statistical settings. In the first setting, a sensible initial estimator of the monotone function ... -
Parameter Identification and Assessment of Independence in Multivariate Statistical Modeling
We are interested in the extent to which, possibly causal, relationships can be statistically quantified from multivariate data obtained from a system of random variables. In the ideal setting, we would begin with refined ... -
Phylogenetic Stochastic Mapping
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 ... -
Portfolio Optimization with Tail Risk Measures and Non-Normal Returns
(2010-08-20)The traditional Markowitz mean-variance portfolio optimization theory uses volatility as the sole measure of risk. However, volatility is flawed both intuitively and theoretically: being symmetric it does not differentiate ... -
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 ... -
Preferential sampling and model checking in phylodynamic inference
Estimating population size fluctuations is one of the key tasks in Ecology. Traditional sampling based approaches to this task have limitations when populations of interest are extinct or are hard to reach, as is the case ... -
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 ... -
Progress in nonparametric minimax estimation and high dimensional hypothesis testing
This dissertation is divided into two parts. In the first part, we study minimax estimation of functions and functionals in nonparametric regression models. The investigation of statistical limits in such models deepens ... -
Projection and Estimation of International Migration
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 ...