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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas
Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas
Graduate Theses and Dissertations
Over the last several decades, plastic waste has gradually accumulated while slowly degrading in terrestrial and oceanic environments. Recently, there has been an increased effort to identify the possible sources of plastic to understand how they affect vulnerable beaches. This issue is of particular concern in the Gulf of Mexico due to the presence of oil, natural gas, and plastic production. In this thesis, we expand upon existing Bayesian plastic attribution models and develop a rigorous statistical framework to map observed beached microplastics to their sources. Within this framework, we combine Lagrangian backtracking simulations of floating particles using nurdle beaching …
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown
Graduate Theses and Dissertations
Single case research design (SCRD) is a common methodology used across clinical disciplines to determine treatments effectiveness by comparing treatment conditions to baseline conditions in individual cases, usually among researchers working with smaller samples. Although popular within behavioral disciplines such as special education and behavioral analysis, studies have begun to emerge in counseling. However, guidance and current understanding of the use of SCRD in counseling is limited. A content analysis of counseling journals from 2003 to 2014 yielded only 7 studies using SCRD. In 2015, the flagship counseling journal, Journal of Counseling and Development, published a special issue on the …
Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto
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 …
Aberrant Responding With Underlying Dominance And Unfolding Response Processes: Examining Model Fit And Performance Of Person-Fit Statistics, Jennifer A. Reimers
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 …
Evaluating The Efficiency Of Markov Chain Monte Carlo Algorithms, Thuy Scanlon
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 …
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 …
Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn
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 …
Development Of An Effect Size To Classify The Magnitude Of Dif In Dichotomous And Polytomous Items, James D. Weese
Development Of An Effect Size To Classify The Magnitude Of Dif In Dichotomous And Polytomous Items, James D. Weese
Graduate Theses and Dissertations
A standardized effect size for the SIBTEST/POLYSIBTEST procedure is proposed, allowing for Differential Item Functioning (DIF) to be classified with a single set of DIF heuristics regardless of whether data are dichotomous or polytomous. This proposed standardized effect size accounts for both variability in responses and whether participants are included in the SIBTEST/POLYSIBTEST calculations. First, a new set of unstandardized effect size heuristics are established for dichotomous data that are more aligned with Educational Testing Service (ETS) standards using two and three parameter logistic (2PL and 3PL) models. Second, a standardized effect size is proposed and compared to other DIF …
Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek
Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek
Graduate Theses and Dissertations
Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear models, …
Models For Data Analysis In Accelerated Reliability Growth, Cesar Alexander Ruiz Torres
Models For Data Analysis In Accelerated Reliability Growth, Cesar Alexander Ruiz Torres
Graduate Theses and Dissertations
This work develops new methodologies for analyzing accelerated testing data in the context of a reliability growth program for a complex multi-component system. Each component has multiple failure modes and the growth program consists of multiple test-fix stages with corrective actions applied at the end of each stage. The first group of methods considers time-to-failure data and test covariates for predicting the final reliability of the system. The time-to-failure of each failure mode is assumed to follow a Weibull distribution with rate parameter proportional to an acceleration factor. Acceleration factors are specific to each failure mode and test covariates. We …
Measuring Sexual Excitation And Sexual Inhibition In A Dutch-Speaking Sample, Malachi Willis
Measuring Sexual Excitation And Sexual Inhibition In A Dutch-Speaking Sample, Malachi Willis
Graduate Theses and Dissertations
Background: Individual differences in sexual excitation and sexual inhibition are important predictors of sexual functioning. Psychometric instruments for these aspects of sexual response were originally developed separately for men (Sexual Inhibition /Sexual Excitation Scales [SIS/SES]) and women (Sexual Excitation/Sexual Inhibition Inventory for Women [SESII-W]). These measures were then adapted to function similarly in samples comprising both men and women (Sexual Inhibition/Sexual Excitation Scales-Short Form [SIS/SES-SF] and Sexual Excitation/Sexual Inhibition Inventory for Women and Men [SESII-W/M], respectively). No published study to our knowledge has administered the SIS/SES and SESII-W/M questionnaires to a sample of both women and men. In the present …
Effect Of Cross-Validation On The Output Of Multiple Testing Procedures, Josh Dallas Price
Effect Of Cross-Validation On The Output Of Multiple Testing Procedures, Josh Dallas Price
Graduate Theses and Dissertations
High dimensional data with sparsity is routinely observed in many scientific disciplines. Filtering out the signals embedded in noise is a canonical problem in such situations requiring multiple testing. The Benjamini--Hochberg procedure using False Discovery Rate control is the gold standard in large scale multiple testing. In Majumder et al. (2009) an internally cross-validated form of the procedure is used to avoid a costly replicate study and the complications that arise from population selection in such studies (i.e. extraneous variables). I implement this procedure and run extensive simulation studies under increasing levels of dependence among parameters and different data generating …
Bayesian Model For Detection Of Outliers In Linear Regression With Application To Longitudinal Data, Zahraa Al-Sharea
Bayesian Model For Detection Of Outliers In Linear Regression With Application To Longitudinal Data, Zahraa Al-Sharea
Graduate Theses and Dissertations
Outlier detection is one of the most important challenges with many present-day applications. Outliers can occur due to uncertainty in data generating mechanisms or due to an error in data recording/processing. Outliers can drastically change the study's results and make predictions less reliable. Detecting outliers in longitudinal studies is quite challenging because this kind of study is working with observations that change over time. Therefore, the same subject can produce an outlier at one point in time produce regular observations at all other time points. A Bayesian hierarchical modeling assigns parameters that can quantify whether each observation is an outlier …
Monte Carlo Methods In Bayesian Inference: Theory, Methods And Applications, Huarui Zhang
Monte Carlo Methods In Bayesian Inference: Theory, Methods And Applications, Huarui Zhang
Graduate Theses and Dissertations
Monte Carlo methods are becoming more and more popular in statistics due to the fast development of efficient computing technologies. One of the major beneficiaries of this advent is the field of Bayesian inference. The aim of this thesis is two-fold: (i) to explain the theory justifying the validity of the simulation-based schemes in a Bayesian setting (why they should work) and (ii) to apply them in several different types of data analysis that a statistician has to routinely encounter. In Chapter 1, I introduce key concepts in Bayesian statistics. Then we discuss Monte Carlo Simulation methods in detail. Our …