Physical Sciences and Mathematics Commons^™

Bayesian Experimental Design For Control And Surveillance In Epidemiology, Bren Case

Graduate College Dissertations and Theses

Effective public health interventions must balance an array of interconnected challenges, and decisions must be made based on scientific evidence from existing information. Building evidence requires extrapolating from limited data using models. But when data are insufficient, it is important to recognize the limitations of model predictions and diagnose how they can be improved. This dissertation shows how principles from Bayesian experimental design can be applied to surveillance and control efforts to allow researchers to get more out of their data and direct limited resources to best effect. We argue a Bayesian perspective on data gathering, where design decisions are …

Applications Of Bayesian Hierarchical Detection Models, Emily Beasley

Graduate College Dissertations and Theses

Bayesian hierarchical detection models are useful for addressing uncertainty in datasets in the form of detection error and can be adapted to a variety of research questions. This dissertation uses three case studies to highlight advantages of Bayesian hierarchical detection models: 1) using prior information to model undetected species, 2) efficiently modeling a naturally hierarchical system, and 3) correcting for observation bias in two interconnected ecological metrics for effective disease management.Detection error can bias ecological observations, especially when a species is never detected during sampling. In many communities, the probable identity of these species is known from previous research, but …

Estimation In Generalized Estimating Equation Measurement Error Models Using Instrumental Variables/ Estimating The Cardinality Of Latent Defective Edges In Hypergraphs, Damin Zhu

Graduate College Dissertations and Theses

This dissertation consists of two studies. The first develops theory for a new method for estimating regression parameters using generalized estimating equations (GEE) with panel data prone to covariate measurement error. The focus is on logistic regression, though the method is applicable to other models. The method requires availability ofinstrumental variables (IV) to identify model parameters. Simulations are performed to assess the performance of the proposed estimator. The method, abbreviated GEEIV, is able to accurately estimate logistic regression parameters masked by measurement error in a variety of population configurations.

In the second study, an algorithm is proposed to estimate the …

High-Resolution Downscaling And Bias-Correction Of Temperature And Precipitation: Advances In Statistical Methods, Maike Holthuijzen

Graduate College Dissertations and Theses

High-resolution, bias-corrected climate data is necessary for climate impact studies and modeling efforts at local scales. General circulation models (GCMs) provide important information about historical and future larger-scale climate trends, but their spatial resolution is too coarse to investigate localized effects of climate processes. Additionally, raw GCM output is characterized by some degree of bias. Two post-processing procedures known as downscaling and bias-correction are typically applied to raw climate model output prior to its use in further modeling applications. Downscaling is the process in which data at a coarse spatial scale is transformed to a fine spatial scale. Bias-correction refers …

Essays On Modeling And Analysis Of Dynamic Sociotechnical Systems, David Rushing Dewhurst

Graduate College Dissertations and Theses

A sociotechnical system is a collection of humans and algorithms that interact under the partial supervision of a decentralized controller. These systems often display in- tricate dynamics and can be characterized by their unique emergent behavior. In this work, we describe, analyze, and model aspects of three distinct classes of sociotech- nical systems: financial markets, social media platforms, and elections. Though our work is diverse in subject matter content, it is unified though the study of evolution- and adaptation-driven change in social systems and the development of methods used to infer this change.

We first analyze evolutionary financial market microstructure …

Smart Classifiers And Bayesian Inference For Evaluating River Sensitivity To Natural And Human Disturbances: A Data Science Approach, Kristen Underwood

Graduate College Dissertations and Theses

Excessive rates of channel adjustment and riverine sediment export represent societal challenges; impacts include: degraded water quality and ecological integrity, erosion hazards to infrastructure, and compromised public safety. The nonlinear nature of sediment erosion and deposition within a watershed and the variable patterns in riverine sediment export over a defined timeframe of interest are governed by many interrelated factors, including geology, climate and hydrology, vegetation, and land use. Human disturbances to the landscape and river networks have further altered these patterns of water and sediment routing.

An enhanced understanding of river sediment sources and dynamics is important for stakeholders, and …

Weighted Networks: Applications From Power Grid Construction To Crowd Control, Thomas Charles Mcandrew

Graduate College Dissertations and Theses

Since their discovery in the 1950's by Erdos and Renyi, network theory (the study of objects and their associations) has blossomed into a full-fledged branch of mathematics.

Due to the network's flexibility, diverse scientific problems can be reformulated as networks and studied using a common set of tools.

I define a network G = (V,E) composed of two parts: (i) the set of objects V, called nodes, and (ii) set of relationships (associations) E, called links, that connect objects in V.

We can extend the classic network of nodes and links by describing the intensity of these associations with weights. …

Predictive Modeling Of Adolescent Cannabis Use From Multimodal Data, Philip Spechler

Graduate College Dissertations and Theses

Predicting teenage drug use is key to understanding the etiology of substance abuse. However, classic predictive modeling procedures are prone to overfitting and fail to generalize to independent observations. To mitigate these concerns, cross-validated logistic regression with elastic-net regularization was used to predict cannabis use by age 16 from a large sample of fourteen year olds (N=1,319). High-dimensional data (p = 2,413) including parent and child psychometric data, child structural and functional MRI data, and genetic data (candidate single-nucleotide polymorphisms, "SNPs") collected at age 14 were used to predict the initiation of cannabis use (minimum six occasions) by age 16. …

An Examination Of College Persistence Factors For Students From Different Rural Communities: A Multilevel Analysis, Andrew Hudacs

Graduate College Dissertations and Theses

Students transitioning into college from public school require more than just academic readiness; they also need the personal attributes that allow them to successfully transition into a new community (Braxton, Doyle, Hartley III, Hirschy, Jones, & McLendon, 2014; Nora, 2002; Nora, 2004; Tinto, 1975). Rural students have a different educational experience than their peers at schools in suburban and urban locations (DeYoung & Howley, 1990; Gjelten, 1982). Additionally, the resources, culture, and educational opportunities at rural schools also vary among different types of rural communities. Although some studies have examined the influence of rural students' academic achievement on college access …

Evolving Spatially Aggregated Features For Regional Modeling And Its Application To Satellite Imagery, Sam Kriegman

Graduate College Dissertations and Theses

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the statistical learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods …

Reviewing Power Outage Trends, Electric Reliability Indices And Smart Grid Funding, Shawn Adderly

Graduate College Dissertations and Theses

As our electric power distribution infrastructure has aged, considerable investment

has been applied to modernizing the electrical power grid through weatherization

and in deployment of real-time monitoring systems. A key question is whether or not

these investments are reducing the number and duration of power outages, leading to

improved reliability.

Statistical methods are applied to analyze electrical disturbance data (from the

Department of Energy, DOE) and reliability index data (from state utility public service

commission regulators) to detect signs of improvement. The number of installed

smart meters provided by several utilities is used to determine whether the number

of smart …

Factors Influencing Mode Choice For Intercity Travel From Northern New England To Major Northeastern Cities, Sean Patrick Neely

Graduate College Dissertations and Theses

Long-distance and intercity travel generally make up a small portion of the total number of trips taken by an individual, while representing a large portion of aggregate distance traveled on the transportation system. While some research exists on intercity travel behavior between large metropolitan centers, this thesis addresses a need for more research on travel behavior between non-metropolitan areas and large metropolitan centers. This research specifically considers travel from home locations in northern New England, going to Boston, New York City, Philadelphia, and Washington, DC. These trips are important for quality of life, multimodal planning, and rural economies. This research …

The Role Of Uncertainty In Categorical Perception Utilizing Statistical Learning In Robots, Nathaniel V. Powell

Graduate College Dissertations and Theses

At the heart of statistical learning lies the concept of uncertainty.

Similarly, embodied agents such as robots

and animals must likewise address uncertainty, as sensation

is always only a partial reflection of reality. This

thesis addresses the role that uncertainty can play in

a central building block of intelligence: categorization.

Cognitive agents are able to perform tasks like categorical perception

through physical interaction (active categorical perception; ACP),

or passively at a distance (distal categorical perception; DCP).

It is possible that the former scaffolds the learning of

the latter. However, it is unclear whether DCP indeed scaffolds

ACP in humans and …

Spatiotemporally Periodic Driven System With Long-Range Interactions, Owen Dale Myers

Graduate College Dissertations and Theses

It is well known that some driven systems undergo transitions when a system parameter is changed adiabatically around a critical value. This transition can be the result of a fundamental change in the structure of the phase space, called a bifurcation. Most of these transitions are well classified in the theory of bifurcations. Among the driven systems, spatiotemporally periodic (STP) potentials are noteworthy due to the intimate coupling between their time and spatial components. A paradigmatic example of such a system is the Kapitza pendulum, which is a pendulum with an oscillating suspension point. The Kapitza pendulum has the strange …

Meta-Analysis Of Studies Investigation Of The Effect Of Smoking Cessation On Impatience, Miriam Claire Dash

Graduate College Dissertations and Theses

(DSM-IV-TR/) nor in withdrawal scales. However, a related term, "impatience" is listed in some nicotine withdrawal scales. (Hughes J. R., Measurements of the Effects of Abstinence from Tobacco: A Qualitative Review, 2007). Although impatience is not a synonym of impulsivity, both share the synonym "impetuous". Therefore, impatience can be considered a measure of impulsivity. Although some reviews of the effect of smoking cessation on impatience have occurred, we know of no quantitative review of prospective studies of whether smoking cessation increases impatience.

Purpose: To evaluate the effect of smoking cessation on impatience as measured by the Minnesota Nicotine Withdrawal Scale-Revised …

An Exploratory Statistical Analysis Of Nasdaq Provided Trade Data, Michael Foley

Graduate College Dissertations and Theses

Since Benoit Mandelbrot's discovery of the fractal nature of financial price series, the quantitative analysis of financial markets has been an area of increasing interest for scientists, traders, and regulators. Further, major technological advances over this time have facilitated not only financial innovations, but also the computational ability to analyze and model markets.

The stylized facts are qualitative statistical signatures of financial market data that hold true across different stocks and over many different timescales. In pursuit of a mechanistic understanding of markets, we look to accurately quantify such statistics. With this quantification, we can test computational market models against …