Statistics and Probability Commons^™

Extensions Of Discrete Choice Experiment Theory For Public Health, Farahnaz Islam

Theses and Dissertations

A discrete choice experiment (DCE) allows researchers to understand how individuals value characteristics of a product or service in hypothetical scenarios and the trade-offs these individuals are willing to make between these characteristics. DCEs quickly gained traction in public health but as more researchers utilized DCEs in broader contexts, several methodological questions have arisen. This dissertation addresses some of these gaps in the literature.

One critique of DCEs is whether individuals would make the same choice in reality as they claimed they would have made in the hypothetical scenario. Perhaps the most efficient way to evaluate the predictive value of …

Orthogonal Arrays And Legendre Pairs, Kristopher N. Kilpatrick

Theses and Dissertations

Well-designed experiments greatly improve test and evaluation. Efficient experiments reduce the cost and time of running tests while improving the quality of the information obtained. Orthogonal Arrays (OAs) and Hadamard matrices are used as designed experiments to glean as much information as possible about a process with limited resources. However, constructing OAs and Hadamard matrices in general is a very difficult problem. Finding Legendre pairs (LPs) results in the construction of Hadamard matrices. This research studies the classification problem of OAs and the existence problem of LPs. In doing so, it makes two contributions to the discipline. First, it improves …

Analytic Case Study Using Unsupervised Event Detection In Multivariate Time Series Data, Jeremy M. Wightman

Theses and Dissertations

Analysis of cyber-physical systems (CPS) has emerged as a critical domain for providing US Air Force and Space Force leadership decision advantage in air, space, and cyberspace. Legacy methods have been outpaced by evolving battlespaces and global peer-level challengers. Automation provides one way to decrease the time that analysis currently takes. This thesis presents an event detection automation system (EDAS) which utilizes deep learning models, distance metrics, and static thresholding to detect events. The EDAS automation is evaluated with case study of CPS domain experts in two parts. Part 1 uses the current methods for CPS analysis with a qualitative …

Statistical Inference On Desirability Function Optimal Points To Evaluate Multi-Objective Response Surfaces, Peter A. Calhoun

Theses and Dissertations

A shortfall of the Derringer and Suich (1980) desirability function is lack of inferential methods to quantify uncertainty. Most articles for addressing uncertainty usually involve robust methods, providing a point estimate that is less affected by variation. Few articles address confidence intervals or bands but not specifically for the Derringer and Suich method. This research provides two valuable contributions to the field of response surface methodology. The first contribution is evaluating the effect of correlation and plane angles on Derringer and Suich optimal solutions. The second contribution proposes and compares 8 inferential methods--both univariate and multivariate--for creating confidence intervals on …

Defining Viable Solar Resource Locations In The Southeast United States Using The Satellite-Based Glass Product, Jolie Kavanagh

Theses and Dissertations

This research uses satellite data and the moment statistics to determine if solar farms can be placed in the Southeast US. From 2001-2019, the data are analyzed in reference to the Southwest US, where solar farms are located. The clean energy need is becoming more common; therefore, more locations than arid environments must be observed. The Southeast US is the main location of interest due to the warm, moist environment throughout the year. This research uses the Global Land Surface Satellite (GLASS) photosynthetically active radiation product (PAR) to determine viable locations for solar panels. A probability density function (PDF) along …

Abm Simulation Model Of A Pandemic For Optimizing Vaccination Strategy, Gibeom Park

Theses and Dissertations

This study presents a process-oriented hybrid model for individuals' immune responses and interactions involving vaccination to describe the trend of contagious disease and estimate the future societal cost. The model considers "recovery" as a non-absorbing state and incorporates various infection stage states including two symptomatic states. To model contagiousness to be consistent with the current pandemic and include that the spread of a disease depends on the mobility of people, we developed an Agent-Based Simulator that fitted to the particular model used in this study and can test various what-if scenarios. We improved the simulator considerably by appying data structures …

Effects Of Macronutrients Intake And Physical Activity On Childhood Obesity Of Hispanic Children, Prosanta Barai

Theses and Dissertations

Obesity has become more ubiquitous during the past few decades, and still, its prevalence is increasing. It is in every population in the world and all regions, including rural parts of low and middle-income countries. In the USA, regardless of age, the severity of obesity is no different from the global trend. Although numerous pieces of literature are available, that tried to find answers to some pressing issues like how obesity can be controlled, but there is little to no study focused on younger children, especially the 4-6-year-old Hispanic population. Our study aimed to determine the causal path among literature …

Neural Networks And Stochastic Differential Equations, Stephanie L. Flores

Theses and Dissertations

Influenced by the seminal work, “Physics Informed Neural Networks” by Raissi et al., 2017, there has been a growing interest in solving and parameter estimation of Nonlinear Partial Differential Equations (PDE) with Deep Neural networks in recent years. In fact, this has broadened the pathways and shed light on deep learning of stochastic differential equations (SDE) and stochastic PDE’s (SPDE).In this work, we intend to investigate the current approaches of solving and parameter estimation of the SDE/SPDE with deep neural networks and the possibility of extending them to obtain more accurate/stable solutions with residual systems and/or generative adversarial neural networks. …

Modified Em Algorithm In Smcure Package Based On Proportional Hazards Mixture Cure Model With Offset Terms, Jiaying Yi

Theses and Dissertations

Mixture cure model is a useful method of survival analysis for population including cured proportion and uncured proportion. The R package SMCURE applies EM algorithm to estimate the coefficients of covariates in the mixture cure model. Although an offset term is specified in the SMCURE statement, the offset term is not appropriately handled in the algorithm. This thesis aims to adjust the EM algorithm for the proportional hazards mixture cure model in the SMCURE package. In addition, the offset term can be specified separately in the incidence part or the latency part. The numerical experiments include simulation study and real …

Statistical Methods For Analyzing Dependence Structures With Applications In Single-Cell Experiments, Zhen Yang

Theses and Dissertations

This dissertation focuses on studying methods in dependence structure analysis. In particular, it consists of two topics: (1) modeling dynamic correlation in zero-inflated bivariate count data; and (2) gene co-expression latent factor analysis for cell-type clustering.

In Chapter 2, a zero-inflated negative binomial model for analyzing the dynamic correlation in zero-inflated bivariate count data is proposed. Interactions between biological molecules in a cell are tightly coordinated and often highly dynamic. As a result of these varying signaling activities, changes in gene co-expression patterns could often be observed. The advancements in next-generation sequencing tech-nologies bring new statistical challenges for studying these …

Complex Functional Joint Models For Longitudinal Electronic Health Record, Siyuan Guo

Theses and Dissertations

Longitudinal measurements are important components in electronic health record (EHR) data. In practice, using longitudinal EHR history is expected to improve the estimation or prediction performance when studying some outcomes of interest, such as binary outcome or time to event outcome. However, the longitudinal observations in EHR data is complex due to irregular and sparse EHR visits. Therefore, modelling longitudinal data and further incorporating them with different types of outcomes is challenge. In this dissertation, we aim to develop methodology to first, describe the pattern of the longitudinal predictors with continuous or binary observations, and second, model the longitudinal predictors …

Statistical Methods For Analyzing Multi-Omics Data: Dependence Structure And Missing Values, Wenda Zhang

Theses and Dissertations

The advancements in high-throughput technologies have made it possible to generate a huge number of "omics'' data, including genomics, proteomics, transcriptomics, epigenomics, metabolomics, and microbiomics. Combining multiple data sources and performing joint analyses with all available information and the phenotypic outcome can reflect various aspects in complex biological systems, such as revealing regulation processes, discovering novel associations between biological entities, and identifying relevant biomarkers for certain diseases or phenotypic outcomes. This dissertation focuses on developing statistical models for analyzing multi-omics data. It is comprised of three topics: (1) integrative analysis for multi-omics data with missing observations in intermediate variables; (2) …

Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low

Theses and Dissertations

The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …

Impact Of Climate Oscillations/Indices On Hydrological Variables In The Mississippi River Valley Alluvial Aquifer., Meena Raju

Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVAA) is one of the most productive agricultural regions in the United States. The main objectives of this research are to identify long term trends and change points in hydrological variables (streamflow and rainfall), to assess the relationship between hydrological variables, and to evaluate the influence of global climate indices on hydrological variables. Non-parametric tests, MMK and Pettitt’s tests were used to analyze trend and change points. PCC and Streamflow elasticity analysis were used to analyze the relationship between streamflow and rainfall and the sensitivity of streamflow to rainfall changes. PCC and MLR analysis …

Evaluating Soil Health Changes Following Cover Crop And No-Till Integration Into A Soybean (Glycine Max) Cropping System In The Mississippi Alluvial Valley, Alexandra Gwin Firth

Theses and Dissertations

The transition of natural landscapes to intensive agricultural uses has resulted in severe loss of soil organic carbon (SOC), increased CO₂ emissions, river depletion, and groundwater overdraft. Despite negative documented effects of agricultural land use (i.e., soil erosion, nutrient runoff) on critical natural resources (i.e., water, soil), food production must increase to meet the demands of a rising human population. Given the environmental and agricultural productivity concerns of intensely managed soils, it is critical to implement conservation practices that mitigate the negative effects of crop production and enhance environmental integrity. In the Mississippi Alluvial Valley (MAV) region of Mississippi, USA, …

Predicting Lower Body Soft Tissue Injuries In American Football With Gps Data, Nicholas Tice

Theses and Dissertations

It is of utmost importance to sports organizations that they keep their players as healthy as possible and contributing to the success of the team. Advancements in technology and investments by sports clubs have allowed researchers to better understand the role of load management in high-level athletes to mitigate injury risk. Through GPS tracking data provided by a collaborating Division I American college football team, we seek to predict lower body soft tissue injuries in future training sessions and reduce the number of potentially avoidable injuries within the organization. The difficulty of analyzing the injury data set is that the …

A Comparison Of Inference Methods In High-Dimensional Linear Regression, Imtiaz Ebna Mannan

Theses and Dissertations

Building confidence/credible intervals for the high-dimensional (p >> n) linear models have been the subject of exploration for many years. In this paper, we explore three specific setups. First, we look at the Bayesian paradigm for the LASSO model. A double-exponential prior has been applied to the regression coefficient and from that, a posterior distribution is derived to get the necessary quantiles to calculate the credible intervals for the regression coefficients. Second, we explore the de-sparsified LASSO estimates, and using its asymptotic normality, we calculate the confidence intervals for the model coefficients. Finally, we incorporate an adaptive LASSO model. To …

Experimental Design On High-Speed Sliding Wear, Irene D. Liew

Theses and Dissertations

The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …

Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas

Theses and Dissertations

Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …

Simulating Autonomous Cruise Missile Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Kyle W. Goggins

Theses and Dissertations

The increasingly sophisticated anti-access area denial (A2AD) threat imposed by the modern integrated air defense system (IADS), coupled with the decreasingly potent advantage provided by high-end stealth platforms, has prompted Air Force senior leaders to invest in radically changing the nature of air power for the year 2030 and beyond. A prominent element of this new vision is weapon swarming, which aims to address this challenge by overwhelming the IADS with huge numbers of low-cost, attritable aerial assets emboldened by autonomous capabilities. This research proposes a framework for classifying the different levels of autonomous capability along three independent dimensions—namely ability …

Predicting Tf33-Pw-100a Engine Failures Due To Oil Issues Using Survival Analyses, Anna M. Davis

Theses and Dissertations

In 2007, the Office of the Assistant Secretary of Defense for Sustainment pushed for the need to transition to a Condition Based Maintenance Plus (CBM ) initiative for weapon systems in the U.S. Department of Defense. The CBM initiative can help increase aircraft availability (AA) for the United States Air Force. There are many reasons where AA can be affected but one such issue is engine availability primarily due to oil issues. Within the CBM perspective, this study examines the risk of a jet engine failure due to an oil issue and attempts to predict an engines time until next …

Examining Failures Of Kc-135s Using Survival Analysis, Vanessa I. R. Unseth

Theses and Dissertations

The United States Air Force manages an inventory of 396 KC-135 Stratotanker aircraft. With mission capability rates falling and total non-mission capability supply rates increasing, it is necessary to take a deeper look at recurrent failures. The study applies non-parametric and semi-parametric survival models to a dataset retrieved from LIMS-EV to look at the duration(s) until failure for the KC-135. Results of non-parametric models show cumulative failure rates increase as sorties or flight hours increase. In addition, semi-parametric models or Cox proportional hazards models with frailty confirm that locations or air bases are not associated with recurrent failures.

Transition Metal Phosphides For High Performance Electrochemical Energy Storage Devices, Amina Saleh

Theses and Dissertations

Electrochemical energy storage technologies are nowadays playing a leading role in the global effort to address the energy challenges. A lot of attention has been devoted to designing hybrid devices known as supercapatteries which combine the merits of supercapacitors (high power density) and rechargeable batteries (high energy density). Transition metal phosphides (TMP) are a rising star for supercapattery anode materials thanks to their high conductivity, metalloid characteristics, and kinetic favorability for fast electron transport. Herein, new TMP-based materials were synthesized for use as supercapattery positive electrodes, via a multifaceted approach to yield devices enjoying concurrently high power and energy densities. …

Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris

Theses and Dissertations

Fully sequential optimal Bayesian experimentation can offer greater utility than both traditional Bayesian designs and greedy sequential methods, but practically cannot be solved due to numerical complexity and continuous outcome spaces. Approximate solutions can be found via approximate dynamic programming, but rely on surrogate models of the expected utility at each trial of the experiment with hand-chosen features or use methods which ignore the underlying geometry of the space of probability distributions. We propose the use of Gaussian process models indexed on the belief states visited in experimentation to provide utility-agnostic surrogate models for approximating Bayesian optimal sequential designs which …

Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee

Theses and Dissertations

Primary Care is on the frontlines of healthcare, thus they see the most diverse set of patients. In order to achieve high functioning primary care, a practice must establish empanelment, the pairing of patients to providers. Enumeration of empanelment, or estimating panel sizes, helps ensure that the demands of the patients demand the supply of providers and optimize the balance of primary care resources to improve quality of care. Further we can adjust panel sizes by using patient-level data on healthcare utilization and complexity extracted from the electronic medial record to determine the amount of care or burden of work …

Improving College Students’ Views And Beliefs Relative To Mathematics: A Systematic Literature Review Followed By A Multiple Case Mixed Methods Exploration Of The Experiences That Underpin Community College Students’ Attitudes, Self-Efficacy, And Values In Mathematics, Marquita H. Sea

Theses and Dissertations

Mathematics is particularly important due to its relevance in our daily lives. It is a general requirement throughout schooling. Unfortunately, many students openly declare negative views/beliefs regarding math in their personal and academic lives. These in turn, negatively influence students’ achievement related behaviors and outcomes. First, a systematic literature review was conducted to determine what types of studies/initiatives have aimed to enhance students’ views/beliefs relative to mathematics, including domain general and specific perceptions of math as well as their judgements of who is successful in mathematics and if they themselves can be successful. Specifically, the review centered on the components …

Estimating The Statistics Of Operational Loss Through The Analyzation Of A Time Series, Maurice L. Brown

Theses and Dissertations

In the world of finance, appropriately understanding risk is key to success or failure because it is a fundamental driver for institutional behavior. Here we focus on risk as it relates to the operations of financial institutions, namely operational risk. Quantifying operational risk begins with data in the form of a time series of realized losses, which can occur for a number of reasons, can vary over different time intervals, and can pose a challenge that is exacerbated by having to account for both frequency and severity of losses. We introduce a stochastic point process model for the frequency distribution …

Role Of Inhibition And Spiking Variability In Ortho- And Retronasal Olfactory Processing, Michelle F. Craft

Theses and Dissertations

Odor perception is the impetus for important animal behaviors, most pertinently for feeding, but also for mating and communication. There are two predominate modes of odor processing: odors pass through the front of nose (ortho) while inhaling and sniffing, or through the rear (retro) during exhalation and while eating and drinking. Despite the importance of olfaction for an animal’s well-being and specifically that ortho and retro naturally occur, it is unknown whether the modality (ortho versus retro) is transmitted to cortical brain regions, which could significantly instruct how odors are processed. Prior imaging studies show different …

The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna

Theses and Dissertations

This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …

Comparison Of Statistical Methods For Modeling Count Data With An Application To Length Of Hospital Stay, Gustavo A. Fernandez

Theses and Dissertations

Hospital length of stay (LOS) is a key indicator of hospital care management efficiency, cost of care, and hospital planning. Therefore, understanding hospital LOS variability is always an important healthcare focus. Hospital LOS data are count data, with discrete and nonnegative values, typically right-skewed, and often exhibiting excessive zeros. Numerous studies have been conducted to model hospital LOS to identify significant predictors contributing to its variability. Many researchers have used linear regression with or without logarithmic transformation of the outcome variable LOS, or logistic regression on a dichotomized LOS. These regression methods usually violate models’ assumptions and are subject …