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 …
Examining The Effect Of Word Embeddings And Preprocessing Methods On Fake News Detection,
2023
University of Nebraska-Lincoln
Examining The Effect Of Word Embeddings And Preprocessing Methods On Fake News Detection, Jessica Hauschild
Department of Statistics: Dissertations, Theses, and Student Research
The words people choose to use hold a lot of power, whether that be in spreading truth or deception. As listeners and readers, we do our best to understand how words are being used. There are many current methods in computer science literature attempting to embed words into numerical information for statistical analyses. Some of these embedding methods, such as Bag of Words, treat words as independent, while others, such as Word2Vec, attempt to gain information about the context of words. It is of interest to compare how well these various methods of translating text into numerical data work specifically …
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 …
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 …
A Generalized Family Of Exponentiated Composite Distributions With Applications To Insurance And Survival Data,
2023
University of Nevada, Las Vegas
A Generalized Family Of Exponentiated Composite Distributions With Applications To Insurance And Survival Data, Bowen Liu
UNLV Theses, Dissertations, Professional Papers, and Capstones
The concept of composite distributions was proposed in the early 2000s as a good parametric solution to model the data with heavy tails. Since the concept was proposed, it has been widely used in different areas, such as modeling insurance claim size data, predicting the risk measures in insurance data analysis, fitting survival time data, and modeling precipitation data. While a lot of the composite distributions demonstrated great performances in real applications, many commonly used composite distributions such as the inverse gamma-Pareto (IGP) or exponential-Pareto (EP), did not demonstrate great performances when fitting to several particular data sets. In order …
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 …
A Brascamp-Lieb–Rary Of Examples,
2023
Macalester College
A Brascamp-Lieb–Rary Of Examples, Anina Peersen
Mathematics, Statistics, and Computer Science Honors Projects
This paper focuses on the Brascamp-Lieb inequality and its applications in analysis, fractal geometry, computer science, and more. It provides a beginner-level introduction to the Brascamp-Lieb inequality alongside re- lated inequalities in analysis and explores specific cases of extremizable, simple, and equivalent Brascamp-Lieb data. Connections to computer sci- ence and geometric measure theory are introduced and explained. Finally, the Brascamp-Lieb constant is calculated for a chosen family of linear maps.
Mixing Measures For Trees Of Fixed Diameter,
2023
Macalester College
Mixing Measures For Trees Of Fixed Diameter, Ari Holcombe Pomerance
Mathematics, Statistics, and Computer Science Honors Projects
A mixing measure is the expected length of a random walk in a graph given a set of starting and stopping conditions. We determine the tree structures of order n with diameter d that minimize and maximize for a few mixing measures. We show that the maximizing tree is usually a broom graph or a double broom graph and that the minimizing tree is usually a seesaw graph or a double seesaw graph.
Gentrification And Crime In The Twin Cities: Insights And Challenges Through A Statistical Lens,
2023
Macalester College
Gentrification And Crime In The Twin Cities: Insights And Challenges Through A Statistical Lens, Erin G. Franke
Mathematics, Statistics, and Computer Science Honors Projects
Gentrification is a complex process of urban redevelopment that typically involves an in-migration of educated people to neighborhoods experiencing a period of disinvestment. While gentrification is widely regarded for its potential to displace long-time businesses and residents of the neighborhood, its impact on crime is highly controversial. There is not a consensus on the relationship between gentrification and crime across criminological theory and past statistical studies have also shown contradictory results. Measuring gentrification on the tract level with census data, we seek to understand gentrification’s relationship with violent crime and theft in the Twin Cities. Using a Poisson model with …
A Machine Learning Approach To Obese-Inflammatory Phenotyping,
2023
The University of Texas Rio Grande Valley
A Machine Learning Approach To Obese-Inflammatory Phenotyping, Tania Mayleth Vargas
Theses and Dissertations
Obesity is the accumulation of an abnormal, or excessive, amount of fat in the body, which can have negative effects on overall health. This excess accumulation of macronutrients in adipose tissue can cause the release of inflammatory mediators, leading to a proinflammatory state. Inflammation is a known risk factor for various health conditions, including cardiovascular diseases, metabolic syndrome, and diabetes. This study sought to examine the use of data mining methods, particularly clustering algorithms, to identify inflammatory biomarker phenotypes and their association with obesity in a local adolescent population. The algorithms evaluated in this study included: k-means, Ward's hierarchical …
Bayesian Semi-Mechanistic Dose-Finding Designs For Phase I Oncology Trials,
2023
The University of Texas MD Anderson Cancer Center
Bayesian Semi-Mechanistic Dose-Finding Designs For Phase I Oncology Trials, Chao Yang
Dissertations and Theses (Open Access)
Bayesian adaptive designs are getting more popular in research and in practice because they are flexible and efficient in evaluating an experimental drug. In oncology, despite the great advances in novel dose-finding designs, the high failure rates of clinical cancer drug development from phase I to III trials call for further improvements on novel designs, in addition to the need to promote and adopt novel designs in practice. Because anticancer agents often have a narrow therapeutic index, an accurate identification of the maximum tolerated dose (MTD) in a phase I trial is crucial for identifying a tolerable and efficacious dose …
Flexible Models For The Estimation Of Treatment Effect,
2023
University of Texas at El Paso
Flexible Models For The Estimation Of Treatment Effect, Habeeb Abolaji Bashir
Open Access Theses & Dissertations
Estimation of treatment effect is an important problem which is well studied in the literature. While the regression models are one of the most commonly used techniques for the estimation of treatment effect, they are prone to model misspecification. To minimize the model misspecification bias, flexible nonparametric models are introduced for the estimation. Continuing this line of research, we propose two flexible nonparametric models that allow the treatment effect to vary across different levels of covariates. We provide estimation algorithms for both these models. Using simulations and data analysis, we illustrate the usefulness of the proposed methods.
Generalized Additive Model Using Marginal Integration Estimation Techniques With Interactions,
2023
University of Texas at El Paso
Generalized Additive Model Using Marginal Integration Estimation Techniques With Interactions, Tahiru Mahama
Open Access Theses & Dissertations
Marginal Integration (MI) is a statistical method that is extensively employed to estimatecomponent functions of the nonparametric additive models. The shortcoming of the purely additive model is that interaction between predictor variables is often ignored, and it may produce poor performance in some real applications. As a result, this research considers the second-order interactions in the regression models. The primary objective is to use marginal integration techniques to estimate the nonparametric additive functions. We compare this model with other models/estimators such as the Generalized Additive Model (GAM), Generalized Additive Model with Selection (GAMSEL), Robust Marginal Integration (RMI), Ordinary Least Squares …
Spatially Adaptive Estimation Of Spectrum,
2023
University of Texas at El Paso
Spatially Adaptive Estimation Of Spectrum, Yi Xie
Open Access Theses & Dissertations
A time series may be analyzed either in the time or in the frequency domain. When working in the frequency domain, the main objective is to estimate the underlying spectrum. Various approaches have been proposed to this end, but most are based on smoothing the periodogram using a single smoothing parameter across all Fourier frequencies. Such a global smoothing parameter may result in a biased estimate. To improve the estimation, in this paper, we smooth the log periodogram by placing a dynamic shrinkage prior, such that varying degrees of smoothing may be applied to different regions of the Fourier frequencies, …
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”, …
Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data.,
2023
University of Texas at El Paso
Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data., Peter Kwadwo Asante
Open Access Theses & Dissertations
This dissertation aims to assess the performance of Ornstein-Uhlenbeck-type models by examining the fractal characteristics of time series data from various sources, including finance, volcanic and earthquake events, US COVID-19 reported cases and deaths, and two simulated time series with differing properties. The time series data is categorized as either a Gaussian or a Lévy process (Lévy walk or Lévy flight) by using three scaling methods: Rescaled range analysis, Detrended fluctuation analysis, and Diffusion entropy analysis. The outcomes of this analysis indicate that the financial indices are classified as Lévy walks, while the volcanic, earthquake, and COVID-19 data are classified …
Hispanic Human Capital And Financial Aid Application In The West Census Region,
2023
California State University, Monterey Bay
Hispanic Human Capital And Financial Aid Application In The West Census Region, Benjamin Lundy-Paine
Capstone Projects and Master's Theses
As of 2021, very few Hispanic residents in the United States held a college degree in comparison to non-Hispanic residents. Research has shown that, particularly for Hispanic students, financial aid increases college persistence. Hispanic Free Application for Federal Student Aid (FAFSA) submission rates rank among the lowest, preventing many Hispanic students from receiving financial assistance. This issue is most prevalent West Census Region (WCR), where there is the highest concentration of Hispanic residents. To understand what barriers may be preventing Hispanic submission in the WCR this Capstone used logistic regression models to analyze student-level data from the National Center for …
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 …
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 …
Examining Model Complexity's Effects When Predicting Continuous Measures From Ordinal Labels,
2023
Utah State University
Examining Model Complexity's Effects When Predicting Continuous Measures From Ordinal Labels, Mckade S. Thomas
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Many real world problems require the prediction of ordinal variables where the values are a set of categories with an ordering to them. However, in many of these cases the categorical nature of the ordinal data is not a desirable outcome. As such, regression models treat ordinal variables as continuous and do not bind their predictions to discrete categories. Prior research has found that these models are capable of learning useful information between the discrete levels of the ordinal labels they are trained on, but complex models may learn ordinal labels too closely, missing the information between levels. In this …
