Statistics and Probability Commons^™

Transformations Between Rotational And Translational Invariants Formulated In Reciprocal Spaces, Philip R Baldwin

Faculty, Staff and Students Publications

Correlation functions play an important role in the theoretical underpinnings of many disparate areas of the physical sciences: in particular, scattering theory. More recently, they have become useful in the classification of objects in areas such as computer vision and our area of cryoEM. Our primary classification scheme in the cryoEM image processing system, EMAN2, is now based on third order invariants formulated in Fourier space. This allows a factor of 8 speed up in the two classification procedures inherent in our software pipeline, because it allows for classification without the need for computationally costly alignment procedures. In this work, …

Knowledge Discovery On The Integrative Analysis Of Electrical And Mechanical Dyssynchrony To Improve Cardiac Resynchronization Therapy, Zhuo He

Dissertations, Master's Theses and Master's Reports

Cardiac resynchronization therapy (CRT) is a standard method of treating heart failure by coordinating the function of the left and right ventricles. However, up to 40% of CRT recipients do not experience clinical symptoms or cardiac function improvements. The main reasons for CRT non-response include: (1) suboptimal patient selection based on electrical dyssynchrony measured by electrocardiogram (ECG) in current guidelines; (2) mechanical dyssynchrony has been shown to be effective but has not been fully explored; and (3) inappropriate placement of the CRT left ventricular (LV) lead in a significant number of patients.

In terms of mechanical dyssynchrony, we utilize an …

Novel Bayesian Neural Networks And Uncertainty Quantification Of Computational Mechanics Models, Ponkrshnan Thiagarajan

Dissertations, Master's Theses and Master's Reports

Computational and data-driven models suffer from a wide range of uncertainties that impact the reliability of such models. Given the exponential proliferation of machine learning models in real-world systems, establishing a degree of confidence in their predictions becomes paramount. Reliability in predictions takes on utmost significance in domains such as autonomous driving, medical image analysis, etc., where human lives are involved, and inaccuracies in predictions could lead to disastrous outcomes. For these reasons, comprehending and quantifying uncertainties in computational and data-driven models is of utmost importance. A number of techniques have been developed to quantify uncertainties in machine learning models. …

Machine Learning Methods For Prediction Of Human Infectious Virus And Imputation Of Hla Alleles, Xiaoqing Gao

Dissertations, Master's Theses and Master's Reports

This dissertation contains three Chapters. The following is a concise description of each Chapters.

In Chapter 1, we introduced the Random Forest, a machine learning method, to foresee whether a virus is capable of infecting humans. The Covid pandemic informs us the importance of predicting the ability of a zoonotic virus that can infect humans from its genomic sequence. We used the -mer with and as features of a virus to predict if it can affect humans. We further employed the Boruta algorithm to select the important features, then fed those important features into the Random Forest method to train …

Enhancing Control Room Operator Decision Making: An Application Of Dynamic Influence Diagrams In Formaldehyde Manufacturing, Joseph Mietkiewicz, Anders L. Madsen

Articles

Intoday’s rapidly evolving industrial landscape, control room operators must grapple with an ever-growing array of tasks and respon sibilities. One major challenge facing these operators is the potential for task overload, which can lead to decision fatigue and increased reliance on cognitive biases. To address this issue, we propose the use of dynamic influence diagrams (DID) as the core of our decision support system. By monitoring the process over time and identifying anomalies, DIDs can recommend the most effective course of action based on a probabilistic assessment of future outcomes. Instead of letting the operator choose or search for the …

Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao

Dissertations, Master's Theses and Master's Reports

This dissertation includes five Chapters. A brief description of each chapter is organized as follows.

In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.

In Chapter Two, we first illustrate the proposed GPN …

Assessing Arrest & Traffic Stop Patterns In Portland, Me, Jack Mcdevitt Ph.D., George Shaler Mph, Sarah Krichels Goan Mpp, Stephen Abeyta, Carlos Cuevas Phd

Publications

This project examined the available arrest and traffic citation data from Portland Police Department to determine if there is any evidence of disproportionate enforcement activities in the city.

Predicting Convection Configurations In Coupled Fluid-Porous Systems, Matthew Mccurdy, Nicholas J. Moore, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

A ubiquitous arrangement in nature is a free-flowing fluid coupled to a porous medium, for example a river or lake lying above a porous bed. Depending on the environmental conditions, thermal convection can occur and may be confined to the clear fluid region, forming shallow convection cells, or it can penetrate into the porous medium, forming deep cells. Here, we combine three complementary approaches - linear stability analysis, fully nonlinear numerical simulations and a coarse-grained model - to determine the circumstances that lead to each configuration. the coarse-grained model yields an explicit formula for the transition between deep and shallow …

On Kernel-Based Estimator Of Odds Ratio Using Different Stratified Sampling Schemes, Abbas Eftekharian, Hani Samawi, Haresh Rochani

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.

Medical Racism: Comparing Prenatal Care Across Races In The United States, Rubina Cheema

Student Research

Prenatal care describes any care a woman receives during her pregnancy. It is intended to keep both the mother and the child healthy and also to reduce the risk of complications during and after birth. This care is especially important for women with high-risk factors so that doctors and nurses are able to monitor their health and the health of their baby during the duration of their pregnancy. For prenatal care to be most effective, it is imperative to begin prenatal care within the first trimester of a woman's pregnancy. However, in the United States, medical racism creates a major …

Study On Innovation Networks And Its Spillover Effect Of China’S New Energy Automobile Industry, Zhifei Xiong, Wenzhong Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The network spillover effect of knowledge has been playing an increasingly significant role in the development of industrial innovation. The urban cooperation matrix of China’s new energy automobile industry is built based on new energy automobile patent data, and the structure and evolution process of China’s new energy automobile industry are depicted. On this basis, the spatial Dubin model (SDM) is used to calculate the network spillover effect, and its results are compared with the results of spillover effect based on the relationship of spatial contiguity and distance of cities. The results show that the innovation activities of China’s new …

Hamilton Cycles In Bidirected Complete Graphs, Arthur Busch, Mohammed A. Mutar, Daniel Slilaty

Mathematics and Statistics Faculty Publications

Zaslavsky observed that the topics of directed cycles in directed graphs and alternating cycles in edge 2-colored graphs have a common generalization in the study of coherent cycles in bidirected graphs. There are classical theorems by Camion, Harary and Moser, Häggkvist and Manoussakis, and Saad which relate strong connectivity and Hamiltonicity in directed "complete" graphs and edge 2-colored "complete" graphs. We prove two analogues to these theorems for bidirected "complete" signed graphs.

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Maxwell Akonde, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu Sc.D., Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Anwar T. Nerchant, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu, Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …

Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong

Statistical Science Theses and Dissertations

The restricted mean survival time (RMST) is a clinically meaningful summary measure in studies with survival outcomes. Statistical methods have been developed for regression analysis of RMST to investigate impacts of covariates on RMST, which is a useful alternative to the Cox regression analysis. However, existing methods for regression modeling of RMST are not applicable to left-truncated right-censored data that arise frequently in prevalent cohort studies, for which the sampling bias due to left truncation and informative censoring induced by the prevalent sampling scheme must be properly addressed. Meanwhile, statistical methods have been developed for regression modeling of the cumulative …

Mitigation Impact Of Statewide Non-Pharmaceutical Policies On Covid-19: An Application Of Infectious Disease Transmission Model And Partially Observed Markov Process To New Mexico, Xingya Ma

Mathematics & Statistics ETDs

This thesis is an application of epidemiological models for infectious disease transmission and the use of partially observed Markov process (POMP) for model fitting. It focuses on COVID-19 pandemic in the state of New Mexico. The analysis covered March 2020 to June 2021. Daily data of COVID19 cases and deaths and a daily index of eleven statewide government non-pharmaceutical intervention (NPI) policies were collected from six public sources and were validated. These data were integrated through the Susceptible-Exposed-Infected-Removed (SEIR) model. Estimated daily transmission rates between the model compartments quantify the impact of the mitigation policies, and show that transmission rates …

Socio‑Economic Inequalities In Minimum Dietary Diversity Among Bangladeshi Children Aged 6–23 Months: A Decomposition Analysis, Satyajit Kundu, Pranta Das, Ashfikur Rahman, Hasan Al Banna, Kaniz Fatema, Akhtarul Islam, Shobhit Srivastava, T. Muhammad, Rakhi Dey, Ahmed Hossain

Department of Statistics: Faculty Publications

This study aimed to measure the socio-economic inequalities in having minimum dietary diversity (MDD) among Bangladeshi children aged 6–23 months as well as to determine the factors that potentially contribute to the inequity. The Bangladesh Demographic and Health Survey (BDHS) 2017–2018 data were used in this study. A sample of 2405 (weighted) children aged 6–23 months was included. The overall weighted prevalence of MDD was 37.47%. The concentration index (CIX) value for inequalities in MDD due to wealth status was positive and the concentration curve lay below the line of equality (CIX: 0.1211, p < 0.001), where 49.47% inequality was contributed by wealth status, 25.06% contributed by the education level of mother, and 20.41% contributed by the number of ante-natal care (ANC) visits. Similarly, the CIX value due to the education level of mothers was also positive and the concentration curve lay below the line of equality (CIX: 0.1341, p < 0.001), where 52.68% inequality was contributed by the education level of mother, 18.07% contributed by wealth status, and 14.69% contributed by the number of ANC visits. MDD was higher among higher socioeconomic status (SES) groups. Appropriate intervention design should prioritize minimizing socioeconomic inequities in MDD, especially targeting the contributing factors of these inequities.

Dealing With Dimensionality: Problems And Techniques In High-Dimensional Statistics, Cezareo Rodriguez

Arts & Sciences Graduate Student Theses and Dissertations

In modern data analysis, problems involving high dimensional data with more variables than subjects is increasingly common. Two such cases are mediation analysis and distributed optimization. In Chapter 2 we start with an overview of high dimensional statistics and mediation analysis. In Chapter 3 we motivate and prove properties for a new marginal screening procedure for performing high dimensional mediation analysis. This screening procedure is shown via simulation to perform better than benchmark approaches and is applied to a DNA methylation study. In Chapter 4 we construct a cryptosystem that accurately performs distributed penalized quantile regression in the high-dimensional setting …

Contribution To Data Science: Time Series, Uncertainty Quantification And Applications, Dhrubajyoti Ghosh

Arts & Sciences Graduate Student Theses and Dissertations

Time series analysis is an essential tool in modern world statistical analysis, with a myriad of real data problems having temporal components that need to be studied to gain a better understanding of the temporal dependence structure in the data. For example, in the stock market, it is of significant importance to identify the ups and downs of the stock prices, for which time series analysis is crucial. Most of the existing literature on time series deals with linear time series, or with Gaussianity assumption. However, there are multiple instances where the time series shows nonlinear trends, or when the …

Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit

WCBT Faculty Publications

In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Carolina Rudisill, Alexander C. Mclain Ph.D.

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Kernel Estimation Of Spot Volatility And Its Application In Volatility Functional Estimation, Bei Wu

Arts & Sciences Graduate Student Theses and Dissertations

It\^o semimartingale models for the dynamics of asset returns have been widely studied in financial econometrics. A key component of the model, spot volatility, plays a crucial role in option pricing, portfolio management, and financial risk assessment. In this dissertation, we consider three problems related to the estimation of spot volatility using high-frequency asset returns. We first revisit the problem of estimating the spot volatility of an It\^o semimartingale using a kernel estimator. We prove a Central Limit Theorem with an optimal convergence rate for a general two-sided kernel under quite mild assumptions, which includes leverage effects and jumps of …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Caroline Rudisill, Alexander C. Mclain

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Survival Of Epithelial Ovarian Cancer In Black Women: A Society To Cell Approach In The African American Cancer Epidemiology Study (Aaces), Joellen M. Schildkraut, Courtney Johnson, Lauren F. Dempsey, Bo Qin, Paul Terry, Maxwell Akonde, Edward S. Peters, Hannah Mandle, Michele L. Cote, Lauren Peres, Patricia Moorman, Ann G. Schwartz, Micheal Epstein, Jeffrey Marks, Melissa Bondy, Andrew B. Lawson, Anthony Alberg, Elisa V. Bandera

Faculty Publications

Purpose

The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC.

Methods

AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010–2015) are presented.

Results …

Truncated Realized Variations Of Lévy Models: Optimality, Debiasing, And Implementation Approaches, Yuchen Han

Arts & Sciences Graduate Student Theses and Dissertations

Statistical inference for stochastic processes under high-frequency observations has been an active research area in econometrics and financial statistics for over twenty years. In this thesis, we consider some aspects related to the estimation of the volatility of an Itô semimartingale in the presence of Lévy-type jumps, which is of fundamental importance in derivatives pricing evaluation, risk management and portfolio allocation. The main technique we use is the Truncated Realized Variation (TRV) that is both rate- and variance-efficient, in the Cramer-Rao lower bound sense, when jumps are of bounded variation.Motivated by recent results that state that the optimal threshold parameter, …

Examining The Impact Of Covid-19 On The Education And Development Of American Students, Riley Fortin '25

Student Research

After the COVID-19 pandemic, the vast majority of American children have fallen behind on core subjects due to the ultimate ineffectiveness of remote learning. This study attempts to discover the degree to which children have fallen behind through the trends in the National Association of Educational Procurement’s two most recent testing years. A database accessed from Google has been analyzed, filtered by state and visualized in tables in order to indicate any possible trends as a result of remote learning brought on by the pandemic. By looking at data in seven different states across the country, there is a notable …

Sexual And Reproductive Health Disparities For Lgbtq+ Patients, Lauren Del Rosario

Student Research

As of 2022, 7.1% of Americans identify as LGBTQ. Members of the LGBTQ+ community in the United States experience greater health disparities than their heterosexual counterparts due to structural inequity: in addition to having minority status within the United States, there is a lack of education and research about LGBTQ+ health-related issues as well as restrictive policies that limit access to health care and other health benefits. As a result, the LGBTQ+ community is more prone to developing certain conditions, have less access to health care, and have worse health outcomes. However, LGBTQ+ visibility has increased dramatically within the last …

Polarization, Media Bias, And General Opinion, Knole Ihle '25

Student Research

This article researches the relationship between three different spheres of influence: party identification, issue selection process in media, and the following changes in public opinion. This relationship was examined through a random sample of news organizations based on a specific issue. The number of articles was then documented for each newspaper and measured against the articles produced apropos to that issue in the previous year. The discrepancy in articles produced is then compared to the succeeding policy shift to determine whether or not there is a correlation between these two relationships. Regarding the relationship between Ukraine-Russia War media and proceeding …

Effects Of A Behavioral Intervention On Physical Activity, Diet, And Health-Related Quality Of Life In Pregnant Women With Elevated Weight: Results Of The Hipp Randomized Controlled Trial, Sarah Wilcox Phd, Jihong Liu, Gabrielle Turner-Mcgrievy Ph.D., Rd, Alycia K. Boutte, Ellen Wingard Msph, Rd, Ld

Faculty Publications

Background

Physical activity (PA), diet, and health-related quality of life (HRQOL) are related to maternal and infant health, but interventions to improve these outcomes are needed in diverse pregnant women with elevated weight.

Methods

Health In Pregnancy and Postpartum (HIPP) was a randomized controlled trial. Women who were pregnant (N=219, 44% African American, 56% white) with overweight or obesity but otherwise healthy were randomized to a behavioral intervention grounded in Social Cognitive Theory (n=112) or to standard care (n=107). The intervention group received an in-depth counseling session, a private Facebook group, and 10 content-based …