A Probabilistic Exploration Of Food Supplementation And Assistance,
2023
Murray State University
A Probabilistic Exploration Of Food Supplementation And Assistance, Logan Mattingly
Honors College Theses
Food insecurity is a stark threat that grips our country and affects households throughout our country. Dietary insufficiency manifests itself in ways that affect health and public safety. According to researchers, individuals who suffer from food insecurity have a higher risk of aggression, anxiety, suicide ideation and depression. These problems tend to occur unequally distributed among those households with lower income. In this work, an exploratory analysis within these data sets will be performed to examine the socio-economic, biographical, nutritional, and geographical principal components of food insecurity among survey participants and how the US Supplemental Nutrition Assistance Program (SNAP) effects …
Fractal Newton Methods,
2023
Missouri University of Science and Technology
Fractal Newton Methods, Ali Akgül, David E. Grow
Mathematics and Statistics Faculty Research & Creative Works
We introduce fractal Newton methods for solving (Formula presented.) that generalize and improve the classical Newton method. We compare the theoretical efficacy of the classical and fractal Newton methods and illustrate the theory with examples.
Fully Decoupled Energy-Stable Numerical Schemes For Two-Phase Coupled Porous Media And Free Flow With Different Densities And Viscosities,
2023
Missouri University of Science and Technology
Fully Decoupled Energy-Stable Numerical Schemes For Two-Phase Coupled Porous Media And Free Flow With Different Densities And Viscosities, Yali Gao, Xiaoming He, Tao Lin, Yanping Lin
Mathematics and Statistics Faculty Research & Creative Works
In this article, we consider a phase field model with different densities and viscosities for the coupled two-phase porous media flow and two-phase free flow, as well as the corresponding numerical simulation. This model consists of three parts: a Cahn-Hilliard-Darcy system with different densities/viscosities describing the porous media flow in matrix, a Cahn-illiard-Navier-Stokes system with different densities/viscosities describing the free fluid in conduit, and seven interface conditions coupling the flows in the matrix and the conduit. Based on the separate Cahn-Hilliard equations in the porous media region and the free flow region, a weak formulation is proposed to incorporate the …
An Integer Garch Model For A Poisson Process With Time-Varying Zero-Inflation,
2023
Missouri University of Science and Technology
An Integer Garch Model For A Poisson Process With Time-Varying Zero-Inflation, Isuru Panduka Ratnayake, V. A. Samaranayake
Mathematics and Statistics Faculty Research & Creative Works
A serially dependent Poisson process with time-varying zero-inflation is proposed. Such formulations have the potential to model count data time series arising from phenomena such as infectious diseases that ebb and flow over time. The model assumes that the intensity of the Poisson process evolves according to a generalized autoregressive conditional heteroscedastic (GARCH) formulation and allows the zero-inflation parameter to vary over time and be governed by a deterministic function or by an exogenous variable. Both the expectation maximization (EM) and the maximum likelihood estimation (MLE) approaches are presented as possible estimation methods. A simulation study shows that both parameter …
Quantifying The Effect Of Socio-Economic Predictors And The Built Environment On Mental Health Events In Little Rock, Ar,
2023
University of Arkansas, Fayetteville
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 …
A Monte Carlo Analysis Of Nonprobability Sampling & Post Hoc Corrections,
2023
Western Kentucky University
A Monte Carlo Analysis Of Nonprobability Sampling & Post Hoc Corrections, Julia Hong
Masters Theses & Specialist Projects
Nonprobability samples are often used in place of probability samples because the former are less trouble and less expensive. Unfortunately, it is difficult to determine how well a sample represents population parameters when using nonprobability samples. Researchers attempt to mitigate the disadvantages of nonprobability sampling by performing post hoc corrections, but this adjustment may not successfully undo the effects of nonprobability sampling. To examine these effects, a Monte Carlo simulation was conducted to create a pseudo-population from which samples were drawn. Forty-one conditions were replicated 10,000 times each, with each sample consisting of 100 observations. A post-stratification adjustment was made …
Identifying And Analyzing Multi-Star Systems Among Tess Planetary Candidates Using Gaia,
2023
Stephen F Austin State University
Identifying And Analyzing Multi-Star Systems Among Tess Planetary Candidates Using Gaia, Katie E. Bailey
Electronic Theses and Dissertations
Exoplanets represent a young, rapidly advancing subfield of astrophysics where much is still unknown. It is therefore important to analyze trends among their parameters to learn more about these systems. More complexity is added to these systems with the presence of additional stellar companions. To study these complex systems, one can employ programming languages such as Python to parse databases such as those constructed by TESS and Gaia to bridge the gap between exoplanets and stellar companions. Data can then be analyzed for trends in these multi-star exoplanet systems and in juxtaposition to their single-star counterparts. This research was able …
Examining Political Discourse On Online 8kun And Reddit Forums,
2023
Utah State University
Examining Political Discourse On Online 8kun And Reddit Forums, Braden Mindrum
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
A recent example of political violence in the United States was that of the January 6, 2021, Capitol attack in connection with the certification of Joseph R. Biden’s victory over Donald J. Trump in the 2020 US presidential election. This thesis analyzes the events of January 6, 2021, through the lens of social media discourse. This thesis presents a workflow that acquired over 5 million 8kun and Reddit posts from various apolitical and political forums in the three months preceding and following the Capitol attack on January 6, 2021. Techniques from text analysis are then used to group forums according …
Investigating The Effect Of Greediness On The Coordinate Exchange Algorithm For Generating Optimal Experimental Designs,
2023
Utah State University
Investigating The Effect Of Greediness On The Coordinate Exchange Algorithm For Generating Optimal Experimental Designs, William Thomas Gullion
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Design of Experiments (DoE) is the field of statistics concerned with helping researchers maximize the amount of information they gain from their experiments. Recently, researchers have been turning to optimal experimental designs instead of classical/catalog experimental designs. One of the most popular algorithms used today to generate optimal designs is the Coordinate Exchange (CEXCH) Algorithm. CEXCH is known to be a greedy algorithm, which means it tends to favor immediate, locally best designs instead of globally optimal designs. Previous research demonstrated that this tradeoff was efficacious in that it reduced the cost of a single run of CEXCH and allowed …
Subgroup Identification Via Interaction Tree And Mixed Model For Repeated Measures With Application To Alzheimer’S Disease,
2023
Washington University in St. Louis
Subgroup Identification Via Interaction Tree And Mixed Model For Repeated Measures With Application To Alzheimer’S Disease, Zhichen Xu
Arts & Sciences Graduate Student Theses and Dissertations
No abstract provided.
Theoretical And Computational Aspects Of Robust Cluster Analysis For Multivariate And High-Dimensional Datasets,
2023
University of Texas at El Paso
Theoretical And Computational Aspects Of Robust Cluster Analysis For Multivariate And High-Dimensional Datasets, Andrews Tawiah Anum
Open Access Theses & Dissertations
Multivariate and high-dimensional datasets typically contain subgroups that may not be immediately apparent. To reveal these groups, cluster analysis is performed. Cluster analysis is an unsupervised machine learning technique commonly employed to partition a dataset into distinct categories referred to as clusters. The k-means algorithm is a prominent distance-based clustering method. Despite overwhelming popularity, the algorithm is not invariant under non-singular affine transformations and is not robust, i.e., can be unduly influenced by outliers. To address these deficiencies, we propose an alternative model-based clustering procedure by minimizing a “trimmed” variant of the negative log-likelihood function. We develop a “concentration step”, …
Dynamics Of Inertial And Non-Inertial Particles In Geophysical Flows,
2023
Montclair State University
Dynamics Of Inertial And Non-Inertial Particles In Geophysical Flows, Nishanta Baral
Theses, Dissertations and Culminating Projects
We consider the dynamics of inertial and non-inertial particles in various flows. We investigate the underlying structures of the flow field by examining their Lagrangian coherent structures (LCS), which are found by computing finitetime Lyapunov exponents (FTLE). We compare the behavior of massless noninertial particles using the velocity fields from four models, the Duffing oscillator, the Bickley jet, the double-gyre flow, and a quasi-geostrophic geophysical flow model, with that of inertial particles. For inertial particles with finite size and mass, we use the Maxey-Riley equation to describe the particle’s motion. We explore the preferential aggregation of inertial particles and demonstrate …
Parameter Optimization For Excitable Cell Models,
2023
Montclair State University
Parameter Optimization For Excitable Cell Models, Amrit Parmar
Theses, Dissertations and Culminating Projects
The electrophysiology of nodose ganglia neurons is of great interest in the analysis of cell membrane currents and action potential behavior. This behavior was initially outlined in the Hodgkin-Huxley conductance model [1] using a system of nonlinear differential equations. Later, Schild et al. [2] developed an extension of the Hodgkin-Huxley model to provide a more exhaustive description of ion channels involved in nodose neuronal action potential activity. We consider a variety of methods to fit the parameters of both the Hodgkin-Huxley and Schild et al. models to an empirical stimulus response dataset. Our methods were validated using synthetic datasets, as …
Effects Of Functional Network Model Definition On Biomarker Outcome Prediction,
2023
Washington University in St. Louis
Effects Of Functional Network Model Definition On Biomarker Outcome Prediction, Xinyang Feng
Arts & Sciences Graduate Student Theses and Dissertations
Machine learning (ML) models are widely used to investigate the human connectome and to predict and understand behavior, emotion, and cognition. Prior research has organized pediatric connectome data using adult functional network models. However, this assumes that adult functional network models are appropriate and useful for prediction developmental outcomes from pediatric connectome data. We hypothesize that the application of adult brain network models could result in poor model fit, limiting the generalizability of results. Here, we test whether prediction of biological age is improved by concordant brain network models matching underlying functional connectome data. To quantify the difference in age …
Uconn Baseball Batting Order Optimization,
2023
University of Connecticut
Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski
Honors Scholar Theses
Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …
Characterization Of Public Opinion On Severity Of Mental Illness And Hiv Based On Individual Traits Using Hierarchical Multi-Category Probit Models,
2023
University of Arkansas, Fayetteville
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 …
Baseball’S Evolution In The 21st Century, And How It Exemplifies Human Response To Change,
2023
Seattle Pacific University
Baseball’S Evolution In The 21st Century, And How It Exemplifies Human Response To Change, Jonathan Sharpe
Honors Projects
The game of baseball has changed a lot in the past twenty years. It can be primarily attributed to the explosion in data analytics and how they are used to evaluate baseball players. This led to different player profiles being preferred and eventually led to the development of players changing. As a result, the strategies employed have also evolved and turned into a different game than seen only a couple of decades ago. This paper will explore the changes that the game has seen. On the other hand, Major League Baseball has also implemented its own changes to try and …
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System,
2023
Clemson University
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin
All Dissertations
Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …
Do Firms Respond To Peer Disclosures? Evidence From Disclosures Of Clinical Trial Results,
2023
HEC Paris
Do Firms Respond To Peer Disclosures? Evidence From Disclosures Of Clinical Trial Results, Vedran Capkun, Yun Lou, Clemens A. Otto, Yin Wang
Research Collection School Of Accountancy
Using data on the registration of clinical trials and the disclosure of trial results, we examine how firms respond to peer disclosures. We find that firms are less likely to disclose their own trial results if the results of a larger number of closely related trials are disclosed by their peers. This relation is stronger if the firms face higher competition (as measured by the number of competing trials). It is weaker if the firms are further along in their research than the peers (as measured by the trials’ phase) and if the peers’ disclosures convey more negative news (as …
The Last Drought Frontier: Building A Drought Index For The State Of Alaska,
2023
University of Nebraska-Lincoln
The Last Drought Frontier: Building A Drought Index For The State Of Alaska, Olivia Campbell
School of Natural Resources: Dissertations, Theses, and Student Research
Drought is characterized by periods of below average precipitation. There are five major types of drought recognized in the literature: meteorological, hydrological, agricultural, socioeconomic, and ecological. A relatively new concept in the drought literature is “snow drought.” A key part of the definition of drought is that it is not always accompanied by extreme heat. This means drought can occur even in cold climates, cold seasons, and higher latitudes and altitudes, like Alaska. Drought is a natural part of climate variability, but Alaska’s climate is changing faster than any other state in the United States. Alaska is no stranger to …
