Statistics and Probability Commons^™

Quantifying The Effect Of Socio-Economic Predictors And The Built Environment On Mental Health Events In Little Rock, Ar, Alfieri Ek, Grant Drawve, Samantha Robinson, Jyotishka Datta

Sociology and Criminology Faculty Publications and Presentations

Law enforcement agencies continue to grow in the use of spatial analysis to assist in identifying patterns of outcomes. Despite the critical nature of proper resource allocation for mental health incidents, there has been little progress in statistical modeling of the geo-spatial nature of mental health events in Little Rock, Arkansas. In this article, we provide insights into the spatial nature of mental health data from Little Rock, Arkansas between 2015 and 2018, under a supervised spatial modeling framework. We provide evidence of spatial clustering and identify the important features influencing such heterogeneity via a spatially informed hierarchy of generalized …

Characterization Of Public Opinion On Severity Of Mental Illness And Hiv Based On Individual Traits Using Hierarchical Multi-Category Probit Models, Md Moinul Ahsan

Graduate Theses and Dissertations

In this thesis, we focus on modeling categorical response variables from public opinion datasets. A hierarchical probit model was used to analyze these different variables. Particularly for multinomial data, we tried different covariate settings to see the model’s performance. For that purpose, we tried two different estimation techniques. The first algorithm uses identified parameters by fixing the first diagonal element of the covariance matrix at 1. The second algorithm uses one unidentifiable parameter and subsequently identifies the parameters by fixing the trace of the covariance matrix. The results from the simulation study confirm that the trace-restricted algorithm performs better with …

Effects Of Land Use On Soil Microbial Communities In Tropical Montane Forests Of Malaysian Borneo, Yang Kai Tang

Graduate Theses and Dissertations

Land use, such as logging and forest conversion to agriculture, can modify soil physicochemical and biological properties, and affect soil health. To understand how land use change can impact soil properties and canopy structure, we used a land use gradient in Malaysian Borneo consisting of six sites, including old growth forests, mixed forests, and agriculture fields. Specifically, we aimed to answer the following questions: (1) How do soil physicochemical properties vary across land use types? (2) Does bacterial diversity and composition vary across different land use types? (3) Does fungal diversity and composition vary across different land use types? We …

Efficient Hierarchical Space-Time Models For Large Areal Datasets With Application To Forest Inventory Mapping Using Remote Sensing Imagery, Md Kamrul Hasan Khan

Graduate Theses and Dissertations

The focus of this dissertation is development of a novel hierarchical framework, that can be used for predictive modeling of Forest Inventory and Analysis (FIA) data over large regions. This dissertation has two significant contributions. Based on a study region in north-central Wisconsin, we analyze satellite imagery, along with a sample of national forest inventory field plots, to monitor and predict changes in forest conditions over time. The auxiliary data from the satellite imagery of this region are relatively dense in space and time, and can be used to learn how forest conditions changed over that decade. However, these records …

Mle And Eap Methods For Estimating Ability Scores For Data Of Varying Sample Size And Item Length, Sahar Taji

Graduate Theses and Dissertations

In this research, the performance of two popular estimators, Maximum Likelihood Estimator(MLE) and Bayesian Expected a Posteriori (EAP) is studied and compared in estimating the latent ability score in an Item Response Theory (IRT) model. The 2-Parameter Logistic (2PL) IRT model which is characterized by difficulty and discrimination item parameters is used to estimate the latent ability scores. Several datasets are generated for variety of sample size and item length values. The Monte-Carlo simulation is used to analyze the performance of the estimators. Results show that MLE produces reliable results with low root mean square error (RMSE) across all datasets. …

Hypothesis Testing And Parameter Estimation In Mixture Cure Models For Cancer Survival Data, Mohammod Mahmudur Rahman

Graduate Theses and Dissertations

In oncology clinical trials, when a treatment is administered to the patient population, a certain subset of patients may respond to the treatment while the other does not. The positive responders with long-term survival are considered “statistically cured” and can be referred to as cured patients or long-term survivors. When a proportion of patients achieve long-term survival, the hazard functions of two arms (control vs. treatment) are no longer proportional. As a result, the traditional log-rank test, which is the most popular test to evaluate the effectiveness of a treatment in clinical trials, tends to lose its power. In this …

Ensemble Tree-Based Machine Learning For Imaging Data, Reza Iranzad

Graduate Theses and Dissertations

In particular medical imaging data, such as positron emission tomography (PET), computed tomography (CT), and fluorescence intravital microscopy (IVM), have become prevalent for use in a wide variety of applications, from diagnostic purposes, tracking diseases' progress, and monitoring the effectiveness of treatments to decision-making processes. The detailed information generated by medical imaging has enabled physicians to provide more comprehensive care. Although numerous machine learning algorithms, especially those used for imaging data, have been developed, dealing with unique structures in imaging data remained a big challenge. In this dissertation, we are proposing novel statistical tree-based methods with more efficient and more …

Hiding In Plain Sight: Accounting For Rate Heterogeneity In Trait Evolution Models, James Boyko

Graduate Theses and Dissertations

Within the last four decades, phylogenetic comparative methods have become the defacto method of analysis for comparative biologists. The availability of high-quality comparative datasets has been matched by an explosion of possible phylogenetic models. In large part, the efforts to increase the realism of phylogenetic comparative methods has been successful as evidenced by their widespread use. To this extensive literature, my contributions are modest. I have focused my dissertation work on two main themes. First, most phenotypic evolution is not independent of other phenotypes. Changes in a particular character may influence changes in another and modeling these characters in isolation …

Improving Computation For Hierarchical Bayesian Spatial Gaussian Mixture Models With Application To The Analysis Of Thz Image Of Breast Tumor, Jean Remy Habimana

Graduate Theses and Dissertations

In the first chapter of this dissertation we give a brief introduction to Markov chain Monte Carlo methods (MCMC) and their application in Bayesian inference. In particular, we discuss the Metropolis-Hastings and conjugate Gibbs algorithms and explore the computational underpinnings of these methods. The second chapter discusses how to incorporate spatial autocorrelation in linear a regression model with an emphasis on the computational framework for estimating the spatial correlation patterns.

The third chapter starts with an overview of Gaussian mixture models (GMMs). However, because in the GMM framework the observations are assumed to be independent, GMMs are less effective when …

Forecasting Razorback Baseball Game Outcomes, Austin Raabe

Information Systems Undergraduate Honors Theses

Despite the disappointing end to the 2021 Arkansas Razorback baseball year, the team’s success provided hog fans something to look forward to next season. While they will be without the 2021 Golden Spikes Award winner, Kevin Kopps, and four All-SEC team selections, the 2022 roster has promising new and returning talent. With fifty percent of the players who played significant time last year coming back (minimum ten hits or ten innings pitched), the arrival of several impact transfers from major conferences, and a recruiting class ranked in the top five according to Perfect Game, there is reason to believe that …

How Blockchain Solutions Enable Better Decision Making Through Blockchain Analytics, Sammy Ter Haar

Information Systems Undergraduate Honors Theses

Since the founding of computers, data scientists have been able to engineer devices that increase individuals’ opportunities to communicate with each other. In the 1990s, the internet took over with many people not understanding its utility. Flash forward 30 years, and we cannot live without our connection to the internet. The internet of information is what we called early adopters with individuals posting blogs for others to read, this was known as Web 1.0. As we progress, platforms became social allowing individuals in different areas to communicate and engage with each other, this was known as Web 2.0. As Dr. …

Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto

Industrial Engineering Undergraduate Honors Theses

The outbreak of COVID-19 has created a major crisis across the world since its start in 2019, and its influence on every realm of society is undeniable. Globally, more than 500 million cases have been recorded since March 2020, with almost 6 million deaths. In the wake of this crisis, many governments and health organizations have taken steps and precautions to mitigate its spread. These steps involve public mandates of information, reducing frequency of personal contact, and use of masks to minimize the risk of transmission. Current access to mobility data released from Google detailing population movements has provided a …

Understanding And Improving The System: The Effects Of Weighting On The Accuracy Of Political Polling In Arkansas, Beck Williams

Political Science Undergraduate Honors Theses

In an effort to increase the accuracy of statewide political polling in Arkansas, we explore the statistical strategy of weighting with a focus on one yearly opinion poll: The Arkansas Poll. We conduct over 70 weighting experiments on the 2016 and 2020 Arkansas Polls using a variety of variables and opinion questions. From these experiments, we find that while some weighted variables tend to create larger changes, weighting typically results in a single-digit percentage change that does not substantially shift or “flip” the majorities. Due to a greater rate of change through weighting in the 2020 Poll compared to the …

The Effects Of Metronomic And Maximum-Tolerated Dose Chemotherapy In Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy And Mrna Expression, Ariel Isaac Mundo Ortiz

Graduate Theses and Dissertations

Colorectal cancer (CRC) continues to be one of the most incident and deadliest types of cancer worldwide. Chemotherapy has proven effective to reduce tumor burden for CRC patients, but there are several disadvantages associated with the use of mainstay maximtolerated dose (MTD) chemotherapeutic strategies. Metronomic chemotherapy (MET) has been developed as an alternative that addresses the shortcomings of maximum-tolerated dose chemotherapy but so far its effectiveness as a neoadjuvant strategy for CRC has not been explored.

This dissertation uses a combined optics and molecular biology approach (using diffuse reflectance spectroscopy and mRNA expression) to study the changes in angiogenesis and …

Multi-Trophic Biodiversity Increases With Increasing Structural Complexity Of Forest Canopy, Ayanna St. Rose

Graduate Theses and Dissertations

Understanding the effects of forest canopy structural complexity on multi-trophic diversity is critical for conserving biodiversity and managing land sustainably. But multi-trophic diversity is often ignored when making decisions about land management due to lack of cost- and time-effective methods to evaluate it. Here, we explored a new method based on widely available remote sensing data to quantify canopy structural complexity and its relationships with multi-trophic biodiversity at landscape scale using 32 forested sites of the National Ecological Observatory Network. We investigated the influence of vertical and horizontal structural complexity of forest canopy on multi-trophic (primary producers, herbivores (beetles), omnivores …

Posterior Predictive Model Checking Of The Hierarchical Rater Model, Nnamdi Chika Ezike

Graduate Theses and Dissertations

Fitting wrongly specified models to observed data may lead to invalid inferences about the model parameters of interest. The current study investigated the performance of the posterior predictive model checking (PPMC) approach in detecting model-data misfit of the hierarchical rater model (HRM). The HRM is a rater-mediated model that incorporates components of the polytomous item response theory (IRT) model, such as the partial credit model (PCM) and generalized partial credit model (GPCM), at the second level of the hierarchy, to model examinees’ responses to performance assessments. To date, the HRM has not been rigorously evaluated using PPMC techniques. Monte Carlo …

Aberrant Responding With Underlying Dominance And Unfolding Response Processes: Examining Model Fit And Performance Of Person-Fit Statistics, Jennifer A. Reimers

Graduate Theses and Dissertations

Researchers have recognized that respondents may not answer items in a way that accurately reflects their attitude or trait level being measured. The resulting response data that deviates from what would be expected has been shown to have significant effects on the psychometric properties of a scale and analytical results. However, many studies that have investigated the detection of aberrant data and its effects have done so using dominance item response theory (IRT) models. It is unknown whether the impacts of aberrant data and the methodology used to identify aberrant responding when using dominance IRT models apply similarly when scales …

Sensory Comparison Of Beer Carbonated Using Forced Carbonation And The Carbo Rock-It, Michala Smith

Biological and Agricultural Engineering Undergraduate Honors Theses

Craft brewing is a growing market which represents over 12% of beer produced in the United States. Dr. G Scott Osborn, PE invented the Carbo Rock-It™ to improve the carbonation process for craft breweries. The invention allows for shorter carbonation time and uses less CO₂, saving companies money and time. Because of the lack of gas losses through bubbling, Osborn theorized that the Carbo Rock-It could also prevent the “stripping of the nose” that can occur in traditional forced carbonation. Existing research supports the mechanism, as beer flavor and aroma volatiles have been detected during the release of …

Data-Driven Statin Initiation Evaluation And Optimization For Prediabetes Population, Muhenned A. Abdulsahib

Graduate Theses and Dissertations

This dissertation develops quantitative models to support medical decision making of statininitiation considering the uncertainty in disease progression for prediabetes patients. A mathematical model is built to help medical decision-makers take action of statin initiation under uncertainty in future prediabetes progressions. The association between cholesterol drug use, such as statin, and elevating glucose level attracted considerable amounts of attention in the literature. Statin effects on glucose vary with respect to different levels of glucose. The first chapter of this dissertation introduces the problem and an overview of the tools that will be used to solve it. In the second chapter …

Statistical Modeling, Learning And Computing For Stochastic Dynamics Of Complex Systems, Mohammadmahdi Hajiha

Graduate Theses and Dissertations

With the recent advances in sensor technology, it is much easier to collect and store streams of system operational and environmental (SOE) data. These data can be used as input to model the underlying behavior of complex engineered systems and phenomenons if appropriate algorithms with well-defined assumptions are developed. This dissertation is comprised of the research work to show the applicability of SOE data when fed into proposed tailored algorithms. The first purposes of these algorithms are to estimate and analyze the reliability of a system as elaborated in Chapter 2. This chapter provides the derivation of closed-form expressions that …

Evaluating The Efficiency Of Markov Chain Monte Carlo Algorithms, Thuy Scanlon

Graduate Theses and Dissertations

Markov chain Monte Carlo (MCMC) is a simulation technique that produces a Markov chain designed to converge to a stationary distribution. In Bayesian statistics, MCMC is used to obtain samples from a posterior distribution for inference. To ensure the accuracy of estimates using MCMC samples, the convergence to the stationary distribution of an MCMC algorithm has to be checked. As computation time is a resource, optimizing the efficiency of an MCMC algorithm in terms of effective sample size (ESS) per time unit is an important goal for statisticians. In this paper, we use simulation studies to demonstrate how the Gibbs …

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

Statistical Modeling For High-Dimensional Compositional Data With Applications To The Human Microbiome, Thy Dao

Graduate Theses and Dissertations

Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology, and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods are needed to analyze this special type of data. This dissertation is motivated by some statistical problems arising in the analysis of compositional data. In particular, we focus on the high-dimensional and over-dispersed setting, where the dimensionality of compositions is greater than the sample size and the dispersion parameter is moderate or large. In …

Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi

Graduate Theses and Dissertations

In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a product to severer-than-normal conditions to expedite the failure process. The resulting lifetime and/or censoring data are often modeled by a probability distribution along with a life-stress relationship. However, if the probability distribution and life-stress relationship selected cannot adequately describe the underlying failure …

Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri

Computer Science and Computer Engineering Undergraduate Honors Theses

In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been …

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing …

Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn

Finance Undergraduate Honors Theses

When talking about financial instruments correlation is often thrown around as a measure of the relation between two securities. An often more useful or tradeable measure is cointegration. Cointegration is the measure of two securities tendency to revert to an average price over time. In other words, cointegration ignores directionality and only cares about the distance between two securities. For a mean reversion strategy such as statistical arbitrage cointegration proves to be a far more reliable statistical measure of mean reversion, and while it is more reliable than correlation it still has its own problems. One thing to consider is …

Peptoid Microsphere Coatings To Improve Performance In Sandwich Elisa Microarrays, Jesse L. Roberts, German R. Perez Bakovic, Shannon L. Servoss

Chemical Engineering Faculty Publications and Presentations

Enzyme-linked immunosorbent assay (ELISA) microarray performance is limited by low assay sensitivity and dynamic range. Increasing the surface area for reagent binding can help to improve performance, but standard techniques such as roughening the surface or adding a polymer coating lead to increased non-specific fluorescence and do not have reproducibly improved performance. Another approach to increase surface area is adding a microsphere coating on the surface. Poly-N-substituted glycine (peptoid) microspheres are ideal for this application due to low immunogenicity, protease-resistance, and biocompatibility. Peptoids are polymers with a backbone similar to peptides, but with the side chains appended to nitrogen rather …

Is Technological Progress A Random Walk? Examining Data From Space Travel, Michael Howell, Daniel Berleant, Hyacinthe Aboudja, Richard Segall, Peng-Hung Tsai

Journal of the Arkansas Academy of Science

Improvement in a variety of technologies can often be successful modeled using a general version of Moore’s law (i.e. exponential improvements over time). Another successful approach is Wright’s law, which models increases in technological capability as a function of an effort variable such as production. While these methods are useful, they do not provide prediction distributions, which would enable a better understanding of forecast quality

Farmer and Lafond (2016) developed a forecasting method which produces forecast distributions and is applicable to many kinds of technology. A fundamental assumption of their method is that technological progress can be modeled as a …

Comparative Evaluation Of Statistical Dependence Measures, Eman Abdel Rahman Ibrahim

Graduate Theses and Dissertations

Measuring and testing dependence between random variables is of great importance in many scientific fields. In the case of linearly correlated variables, Pearson’s correlation coefficient is a commonly used measure of the correlation strength. In the case of nonlinear correlation, several innovative measures have been proposed, such as distance-based correlation, rank-based correlations, and information theory-based correlation. This thesis focuses on the statistical comparison of several important correlations, including Spearman’s correlation, mutual information, maximal information coefficient, biweight midcorrelation, distance correlation, and copula correlation, under various simulation settings such as correlative patterns and the level of random noise. Furthermore, we apply those …