Browsing Statistics by Title
Now showing items 68-87 of 108
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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 ... -
R-squared inference under non-normal 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 ... -
R-squared inference under non-normal 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 ... -
Realized genome sharing in random effects models for quantitative genetic traits
DNA copies inherited from the same ancestral copy by related individuals are said to be identical by descent (IBD). IBD gives rise to genetic similarities between related individuals. In quantitative genetics, two fundamental ... -
Representation Learning for Partitioning Problems
This dissertation addresses representation learning for partitioning problems. Clustering a set of data points and segmenting a time series of data points are two classical partitioning problems. Nonparametric methods such ... -
A resampling approach to clustering with confidence
(2012-09-13)We propose a method for estimating the number of groups in a data set. Our method is an extension of Generalized Single Linkage clustering (GSL) (Stuetzle and Nugent 2010), a nonparametric clustering method based on the ... -
Robust estimation of factor models in finance
(2005)Standard asset-pricing models entail expressions for expected returns in terms of coefficients relative to risk factors. Methods to estimate premiums of risk factors have, at its core, a single or multiple linear regression ... -
Scalable Learning in Latent State Sequence Models
In this dissertation, we develop scalable learning methods for sequential data models with latent (hidden) states. State space models (SSMs) and recurrent neural networks (RNNs) are popular models for sequential data using ... -
Scalable Manifold Learning and Related Topics
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 ... -
Scalable Methods for the Inference of Identity by Descent
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 ... -
Shape-Constrained Inference for Concave-Transformed Densities and their Modes
(2013-11-14)We consider inference about functions estimated via shape constraints based on concavity. We consider log-concave densities and other “concave-transformed” densities on the real line, where a concave-transformed class is ...