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Full-Text Articles in Statistics and Probability

Opening The Black Box With Regal: A Novel Explainable Ai Approach To Uncover Key Predictors In Search And Rescue Success, Brandon Hyunjun Kim Jun 2025

Opening The Black Box With Regal: A Novel Explainable Ai Approach To Uncover Key Predictors In Search And Rescue Success, Brandon Hyunjun Kim

Master's Theses

The outcome of a search and rescue (SAR) operation is influenced by a complex, non-linear interplay among numerous factors, including geographic context, subject-specific characteristics, and environmental conditions. The high dimensionality and intricate dependencies among these variables pose significant challenges to traditional exploratory modeling approaches, limiting their ability to uncover meaningful patterns and relationships associated with mission success. This study introduces Rules Based Explanations for Generated neighborhoods Around Localized cases (REGAL), a novel adaptation of the Local Interpretable Model-agnostic Explanations (LIME) framework to explain deep multimodal neural networks and what key features it assesses to determine search and rescue success. REGAL …


Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le Jun 2025

Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le

Master's Theses

Exploratory data analysis (EDA) is a method for uncovering the structure and key characteristics of data, often through the use of statistical graphics. These visual tools can reveal patterns and trends, and their effectiveness can be enhanced through interactivity. By enabling users to filter data, zoom, and toggle visual features, interactive plots can accelerate and enrich the EDA process. This study extends a previous graphical study by incorporating an interactive framework. Using a statistical lineup protocol with two target patterns (a linear trend and a clustering trend) participants interacted with plots by toggling various aesthetic features, including cluster coloring, ellipses …


Testing For Broad Alternatives In Stratified Contingency Tables, Nan Mi Jun 2025

Testing For Broad Alternatives In Stratified Contingency Tables, Nan Mi

Dissertations

In medical and social sciences fields, data are measured in terms of discrete categories. The primary question of interest involves the relationship between a set of factors and a set of response variables under studies. Moreover, the distribution of the response variables may be influenced by another set of variables called confounders. The data from such studies are summarized in 3-way tables. The hypothesis we are interested in can be expressed in terms of "no partial association" between the sub-populations and the response levels.

The methods for testing the association or independence in a 2x2 contingency table have been developed, …


Socioeconomic Disparities In Breast Cancer Survival: Examining Potential Mediator Role Of Oncotype Dx(Odx) Test And Stage At Diagnosis Among Hr+/Her2- Breast Cancer Women, Pratibha Shrestha, Qingzhao Yu, Edward S. Peters, Edward Trapido, Mei Chin Hsieh, Tekeda Ferguson, Quyen D. Chu, Xiao Cheng Wu May 2025

Socioeconomic Disparities In Breast Cancer Survival: Examining Potential Mediator Role Of Oncotype Dx(Odx) Test And Stage At Diagnosis Among Hr+/Her2- Breast Cancer Women, Pratibha Shrestha, Qingzhao Yu, Edward S. Peters, Edward Trapido, Mei Chin Hsieh, Tekeda Ferguson, Quyen D. Chu, Xiao Cheng Wu

School of Public Health Faculty Publications

Background: Women with a lower socioeconomic status (SES) have an increased risk of dying from breast cancer (BC) than those with a higher SES. The association of SES with BC survival may be partially mediated by factors such as Oncotype DX (ODX) testing and stage at diagnosis. This study aims to examine SES disparities in survival among HR+/HER2- BC women and to quantify the mediating effects of the ODX test and stage. Methods: We used data from the Louisiana Tumor Registry to identify women aged 20–90 years diagnosed with stage I–II in 2011–2014 and stage I–III in 2015–2017 HR+/HER2- BC …


American Society Of Hematology/International Society On Thrombosis And Haemostasis 2024 Updated Guidelines For Treatment Of Venous Thromboembolism In Pediatric Patients, Paul Monagle, Muayad Azzam, Rachel Bercovitz, Marisol Betensky, Rukhmi Bhat, Tina Biss, Brian Branchford, Leonardo R. Brandão, Anthony K.C. Chan, Vincent E.S. Faustino, Julie Jaffray, Sophie Jones, Hassan Kawtharany, Bryce A. Kerlin, Nicole Kucine, Riten Kumar, Christoph Male, Marie Claude Pelland-Marcotte, Leslie Raffini, Chittalsinh Raulji, Sarah E. Sartain, Clifford M. Takemoto, Cristina Tarango, C. Heleen Van Ommen, Maria C. Velez, Sara K. Vesely, John Wiernikowski, Suzan Williams, Hope P. Wilson, Et Al May 2025

American Society Of Hematology/International Society On Thrombosis And Haemostasis 2024 Updated Guidelines For Treatment Of Venous Thromboembolism In Pediatric Patients, Paul Monagle, Muayad Azzam, Rachel Bercovitz, Marisol Betensky, Rukhmi Bhat, Tina Biss, Brian Branchford, Leonardo R. Brandão, Anthony K.C. Chan, Vincent E.S. Faustino, Julie Jaffray, Sophie Jones, Hassan Kawtharany, Bryce A. Kerlin, Nicole Kucine, Riten Kumar, Christoph Male, Marie Claude Pelland-Marcotte, Leslie Raffini, Chittalsinh Raulji, Sarah E. Sartain, Clifford M. Takemoto, Cristina Tarango, C. Heleen Van Ommen, Maria C. Velez, Sara K. Vesely, John Wiernikowski, Suzan Williams, Hope P. Wilson, Et Al

School of Medicine Faculty Publications

Background: The American Society of Hematology (ASH) guidelines on treatment of pediatric venous thromboembolism (VTE) were published in 2018. In the last 6 years, there has been a 10-fold increase in the number of children involved in VTE treatment trials. Objective: The ASH Committee on Quality and Guidelines agreed to update the pediatric guidelines in conjunction with the International Society on Thrombosis and Haemostasis (ISTH). These ASH/ISTH evidence-based guidelines are intended to support patients, clinicians, and other health care professionals in the management of pediatric patients with VTE. Methods: ASH/ISTH formed a multidisciplinary guideline panel to minimize potential bias from …


Mat 301 - Applied Statistics And Data Analysis, Eric Aragundi May 2025

Mat 301 - Applied Statistics And Data Analysis, Eric Aragundi

Open Educational Resources

Data analysis using standard statistical methods and relevant computer software. Emphasis on real-world data, interpretation, and misinterpretation of computer output.

This syllabus contains open source notebook about data analysis content.


Human Endogenous Retroviruses (Hervs) Associated With Glioblastoma Risk And Prognosis, Harun Mazumder, Hui Yi Lin, Melody Baddoo, Wojciech Gałan, Diana Polania-Villanueva, Chindo Hicks, David Otohinoyi, Francesca Peruzzi, Zbigniew Madeja, Victoria P. Belancio, Erik K. Flemington, Krzysztof Reiss, Monika Rak May 2025

Human Endogenous Retroviruses (Hervs) Associated With Glioblastoma Risk And Prognosis, Harun Mazumder, Hui Yi Lin, Melody Baddoo, Wojciech Gałan, Diana Polania-Villanueva, Chindo Hicks, David Otohinoyi, Francesca Peruzzi, Zbigniew Madeja, Victoria P. Belancio, Erik K. Flemington, Krzysztof Reiss, Monika Rak

School of Medicine Faculty Publications

Emerging evidence suggests expression from human endogenous retrovirus (HERV) loci likely contributes to, or is a biomarker of, glioblastoma multiforme (GBM) disease progression. However, the relationship between HERV expression and GBM malignant phenotype is unclear. Applying several in silico analyses based on data from The Cancer Genome Atlas (TCGA), we derived a locus-specific HERV transcriptome for glioma that revealed 211 HERVs significantly dysregulated in the comparisons of GBM vs. normal brain (NB), GBM vs. low-grade glioma (LGG), and LGG vs. NB. Our analysis supported development of a unique HERV scoring algorithm that segregated GBM, LGG, and NB. Interestingly, lower HERV …


Hybrid Graph-Recurrent Architecture For Citation Recommendation Via Future Embedding Forecasting, Mohammad Ausaf Ali Haqqani May 2025

Hybrid Graph-Recurrent Architecture For Citation Recommendation Via Future Embedding Forecasting, Mohammad Ausaf Ali Haqqani

Computer Science and Engineering Theses and Dissertations

The rapid expansion of scientific literature has intensified the challenge of identifying relevant citations, particularly for newly published or under-cited papers. Traditional citation recommendation systems typically model static relationships or respond to past citation activity, offering limited predictive power for emerging works. In response, this thesis presents a temporal modeling framework for citation recommendation that anticipates future scholarly relevance by forecasting the latent representations of academic papers.

Building on prior work that utilized Temporal Graph Networks (TGNs) to model dynamic citation flows, we propose Graph-Time, a hybrid architecture that integrates a Graph Transformer with a GRU-based time series predictor. The …


“Do You Even Lift, Bro?”: Correlates Of Muscle Dysmorphia Symptomatology In Filipino Male University Students, Pamela Paula C. Pioquinto May 2025

“Do You Even Lift, Bro?”: Correlates Of Muscle Dysmorphia Symptomatology In Filipino Male University Students, Pamela Paula C. Pioquinto

UNLV Theses, Dissertations, Professional Papers, and Capstones

Muscle Dysmorphia (MD) is a subtype of Body Dysmorphic Disorder (BDD) and is marked by the desire to increase muscularity and reduce body fat. MD is typically more prevalent among younger male populations, and it often drives comorbid disorders, including substance abuse, eating disorders, and social anxiety. Despite the growing literature on MD, it remains understudied in certain racial/ethnic populations, such as Filipinos. Acculturation, defined as the process in which an individual adopts, acquires, and adapts to a new cultural environment as a result of immigration, influences body image by reshaping an individual’s perceptions of beauty and muscularity standards. Guided …


Associations Of The Medicaid Expansion Policy With Racial/Ethnic Disparities In Breast Cancer Screening And Treatment, James Howard Smith Ii May 2025

Associations Of The Medicaid Expansion Policy With Racial/Ethnic Disparities In Breast Cancer Screening And Treatment, James Howard Smith Ii

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background and Aim. This dissertation examines Medicaid expansion’s effect on breast cancer (BC) screening and treatment disparities in two Medicaid-expanding states (MES) that passed Medicaid expansion (New Jersey and Vermont) relative to two non-expansion states (NES) (Georgia and Wisconsin). It then compares the association of Medicaid expansion to other states that did not undertake this policy on various subgroups, such as minorities by race and ethnicity, income, and age groups. Black women still bear significant BC disparities due to untimely screenings, treatments, and deaths. Therefore, it is critical to investigate how socioeconomic status influences racial/ethnic disparity gaps, given that BC …


Resale Revolution: Trend Implications From Media Presence Transcended To Luxury Retail Markets, Penelope Prochnow May 2025

Resale Revolution: Trend Implications From Media Presence Transcended To Luxury Retail Markets, Penelope Prochnow

Capstone Projects

This study aims to deepen understanding of fashion trend decline from peak popularity to obsolescence, with implications for sustainability and producer profit margins. It investigates how the attributes and media presence of fashion items influence their journey from high-end editorial coverage to resale platforms. Using survival analysis to model trend lifetimes and cosine similarity metrics to compare resale and magazine keyword frequencies, alongside machine learning for price prediction, the study uncovers critical temporal patterns. Results show that resale trends reflect magazine content with a lag of approximately 18 to 30 months and draw from long-wave revivals spanning 6 to 14 …


On The H-Property For Step-Graphons: Residual Case, Wanting Gao May 2025

On The H-Property For Step-Graphons: Residual Case, Wanting Gao

McKelvey School of Engineering Graduate Student Theses & Dissertations

We investigate the H-property for step-graphons. Specifically, we sample graphs Gn on n nodes from a step-graphon and evaluate the probability that Gn has a Hamiltonian decomposition in the asymptotic regime as n → ∞. It has been shown in Belabbas and Chen (2023); Belabbas et al. (2021) that for almost all step-graphons, this probability converges to either zero or one. We focus in this paper on the residual case where the zero-one law does not apply. We show that the limit of the probability still exists and provide an explicit expression of it. We present a complete proof of …


Evaluating Predictive Models For Predicting Total Score Of Beef Carcasses, Emmanuel Forson May 2025

Evaluating Predictive Models For Predicting Total Score Of Beef Carcasses, Emmanuel Forson

Electronic Theses and Dissertations

The beef industry plays a vital role in global agriculture, with carcass quality and consumer preference being key determinants of market success. This thesis examines predictive modeling techniques for estimating the Total Score of beef carcasses, a composite measure representing yield and quality, primarily used by the Nebraska Cattlemen Association. Using data from the Nebraska Cattlemen’s Foundation Retail Value Steer Challenge (2000–2023), the study compares the performance of First Order Multiple Linear Regression (MLR) with three machine learning techniques: K-Nearest Neighbors (KNN), Random Forest, and Gradient Boosting Machine (GBM).

The analysis focuses on six key predictors: Hot Carcass Weight, Back …


Bayesian Statistics: Origins And Applications, Evelyn Pulla May 2025

Bayesian Statistics: Origins And Applications, Evelyn Pulla

Publications and Research

Bayesian Statistics applies Bayes' Theorem to update beliefs through new evidence. In this project, I explored how Bayesian Statistics applies into real supporting decision-making under uncertainty. By solving problems using data, I was able to realize how prior knowledge and evidence collaborate to make better conclusions. The project also demonstrates how Bayesian reasoning corrects our intuition to make decisions based on logical reasoning. Through this project, I was able to learn why using probability to make informed decisions matters both in science and real life.


Challenges Us Study Abroad Students Face When Acculturating To A Foreign Food Environment, Sydney C. Davis May 2025

Challenges Us Study Abroad Students Face When Acculturating To A Foreign Food Environment, Sydney C. Davis

Honors Theses

Studying abroad presents a unique opportunity for college students to immerse themselves in new cultures, including experiencing different food environments and dietary customs. However, adapting to a foreign food culture can pose various challenges that impact students’ overall health, eating behaviors, and study abroad experiences. The purpose of this study to develop a survey instrument designed to investigate the extent to which U.S. study abroad students embrace, accept, and face challenges with different aspects of Italian food culture, using the Social Ecological Model (SEM) as a guiding framework. Initial survey items were developed with information obtained from focus group discussions …


Statistics - What Does My Data Say About Me?, Taylor Gadsden-Deterville May 2025

Statistics - What Does My Data Say About Me?, Taylor Gadsden-Deterville

Student Scholar Symposium Abstracts and Posters

For my Introduction to Statistics Class, I have been tasked with collecting unique, personal data to give insight into my daily routine. I decided to record nine different outcomes (two qualitative and seven quantitative). On February 6, 2025, I began with a blank Excel sheet, and so far, I have 57 full days of data collected. I will continue monitoring my findings for the remainder of the Spring 2025 Semester. Per my project instructions, I must include tables and graphs for my qualitative and quantitative outcomes. So far, I have collected daily quantitative data on my screen time (Instagram and …


Using A Pharmacokinetic Model To Design And Evaluate An Early Ctdna Biomarker For Response To Targeted Therapy, Aaron Li May 2025

Using A Pharmacokinetic Model To Design And Evaluate An Early Ctdna Biomarker For Response To Targeted Therapy, Aaron Li

Spora: A Journal of Biomathematics

Early prediction of response to therapy or lack thereof can help physicians plan treatment more efficiently. Biomarkers based on circulating tumor DNA (ctDNA) are promising. However, biomarkers beyond direct comparison to baseline have not been thoroughly explored. We develop a model for ctDNA shedding under targeted therapy that incorporates pharmacokinetics. Using a simulated cohort of virtual patients with varied parameters, we define and analyze a biomarker based on ctDNA samples at baseline, 12 hours, and 24 hours after initiation of treatment. The biomarker identified patients who would achieve partial or complete response with high sensitivity and specificity and was able …


Two-Sample Bi-Directional Causality Between Two Traits With Some Invalid Ivs In Both Directions Using Gwas Summary Statistics, Siyi Chen May 2025

Two-Sample Bi-Directional Causality Between Two Traits With Some Invalid Ivs In Both Directions Using Gwas Summary Statistics, Siyi Chen

School of Public Health Faculty Publications

Mendelian randomization (MR) is a widely used method for assessing causal relationships between risk factors and outcomes using genetic variants as instrumental variables (IVs). While traditional MR assumes uni-directional causality, bi-directional MR aims to identify the true causal direction. In uni-directional MR, invalid IVs due to pleiotropy can violate assumptions and introduce biases. In bi-directional MR, traditional MR can be performed separately for each direction, but the presence of invalid IVs poses even greater challenges. We introduce a new bi-directional MR method incorporating stepwise selection (Bidir-SW) designed to address these challenges. Our approach leverages public genome-wide association study (GWAS) datasets …


Modeling Literary Connections: Exploring Transregional Resistance In Dalit Poetry, Antara Bhattacharyay May 2025

Modeling Literary Connections: Exploring Transregional Resistance In Dalit Poetry, Antara Bhattacharyay

Mathematics, Statistics, and Computer Science Honors Projects

Structuring socio-political identities, the caste system (a graded form of hierarchy) remains entrenched in contemporary Indian society. Dalits, marginalized by the caste system, have expressed their resistance through literature, envisioning substantive equality and social change. In this thesis, I draw on digital humanities methods to examine regional variation in translated Dalit poetry from Bengali, Hindi/Urdu, Marathi, and Tamil languages. I utilize topic modeling—a machine learning algorithm that detects latent semantic structures in a text—as a point of departure for poetry analysis. I observe how topic modeling enables newer readings of the poems, revealing regionally resonant and broader Dalit themes.


Contribution Of Various Factors On The Rate Of Traffic Accidents In The Us, Martin Mnatsakanyan May 2025

Contribution Of Various Factors On The Rate Of Traffic Accidents In The Us, Martin Mnatsakanyan

Undergraduate Research Symposium Lightning Talks

Background:

Until 2020, the number of traffic accidents has been steadily decreasing. After 2020, the number started increasing until 2022, then started s lowly decreasing again. Most drivers aren’t fully aware of the reason behind all of these accidents.


Variable Selection In Mixture Cure Models Using Elastic Net Penalty: Application To Covid-19 Data, Aluwani Ramalata, Akim Adekpedjou, Maseka Lesaoana May 2025

Variable Selection In Mixture Cure Models Using Elastic Net Penalty: Application To Covid-19 Data, Aluwani Ramalata, Akim Adekpedjou, Maseka Lesaoana

Mathematics and Statistics Faculty Research & Creative Works

In survival analysis, it is often assumed that all individuals will eventually experience the event of interest if followed long enough. However, in many real-world scenarios, a subset of individuals remains event-free indefinitely. For instance, in clinical studies, some patients never relapse and are considered cured rather than censored. Traditional survival models are inadequate for capturing this heterogeneity. Mixture cure models address this limitation by distinguishing between cured and susceptible individuals while modeling the survival of the latter. A key challenge in mixture cure modeling is selecting relevant covariates, particularly when dealing with time-varying effects. This study develops a penalized …


The Impact Of Maternal Age On The Expression Of Transgenerational Plasticity In Daphnia Pulicaria, Calvin Nguyen May 2025

The Impact Of Maternal Age On The Expression Of Transgenerational Plasticity In Daphnia Pulicaria, Calvin Nguyen

2025 Spring Honors Capstone Projects - Archive

Transgenerational plasticity refers to heritable, non-genetic changes in phenotype that persist across multiple generations and can enhance offspring survivability in variable environments. In Daphnia, increasing maternal age has been associated with maladaptive plasticity. To investigate this relationship, six clones were collected from two Wisconsin lakes and acclimated to laboratory conditions through a common garden rearing process. For each clone, ten replicates were generated and evenly divided between young (clutches 2–4) and old (clutches 5–8) maternal age groups. Offspring were exposed to three dietary treatments for three experimental generations: one fed only green algae, one fed only cyanobacteria (a nutritionally …


The Little Diagram That Could: Geometric Properties And Statistical Applications Of Persistence Diagrams In Topological Data Analysis, Eugene Kler May 2025

The Little Diagram That Could: Geometric Properties And Statistical Applications Of Persistence Diagrams In Topological Data Analysis, Eugene Kler

McKelvey School of Engineering Graduate Student Theses & Dissertations

Topological Data Analysis (TDA) is a collection of techniques for data analysis that leverages topological invariants of spaces formed from data points. These methods excel at extracting useful information from noisy or sparse data, making them attractive to many mathematicians, statisticians, and scientists. In this thesis, we explore TDA on three fronts: algebraic foundations, statistical applications, and metric properties. Throughout, the central object of study is the Persistence Diagram (PD), a summary of the changes in homology that occur as one builds simplicial complexes from the data by increasing a parameter.


Statistical Designs For Learning User Preference And Experience, William S. Fisher May 2025

Statistical Designs For Learning User Preference And Experience, William S. Fisher

All Dissertations

For any organization, designing a new product or planning the features of a new service is a complex decision-making process which depends on understanding its users' preferences and the experiences they have with prototypes of the new product or service. Design of experiments (DOE) offers a framework to aid in the modeling and collection of data to learn user preferences and experiences to facilitate this decision-making process. Questions such as ``which of our newly proposed products is preferred most by our customers" and ``which version of our new service results in the highest monthly revenue" can be readily addressed by …


Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee May 2025

Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee

Chemical Engineering Undergraduate Honors Theses

This study investigates the use of derivative-informed Gaussian Process (GP) models to estimate thermodynamic behavior across temperature and density by building a Helmholtz-based equation of state. Argon, a stable monatomic gas, was chosen as a case study within the vapor region. The GP model was trained using values of experimentally measurable properties found by taking first and second derivatives of the original potential function. Results show that while the GP model offered uncertainty quantification and informed thermodynamic behavior, it predicted values that deviated from the ground truth depending on the property. The model exhibited high confidence in regions with substantial …


Deleting Values May Either Increase Or Decrease Variance, David L. Farnsworth May 2025

Deleting Values May Either Increase Or Decrease Variance, David L. Farnsworth

Articles

The impact upon variance when a value is deleted is addressed. It is shown that the cutoff for the deleted value yielding an increase or a decrease in variance is approximately one standard deviation from the mean for a univariate random variable with equally distributed probability on a finite set of elements and for a univariate set of observations. The influence of truncation of the domain for such a discrete random variable and for observations is considered.


Analyzing Sleep Staging And Cognitive Transitions Using Fmrl Time Series Analysis, Qingwen Zeng May 2025

Analyzing Sleep Staging And Cognitive Transitions Using Fmrl Time Series Analysis, Qingwen Zeng

Arts & Sciences Graduate Student Theses and Dissertations

Understanding sleep stages and their underlying cognitive transitions is essential for advancing our knowledge of brain function. While sleep staging has traditionally relied on electroencephalogram (EEG), this study explores the feasibility of classifying sleep stages using only functional Magnetic Resonance Imaging (fMRI) data. We investigate the use of Hidden Markov Models (HMM) and Hierarchical Dirichlet Process Hidden Markov Models (HDP-HMM) to capture temporal brain-state dynamics from task-free fMRI recordings. A series of pipelines—including sliding window, two-stage majority filtering, and prototype-based mapping via the Hungarian algorithm—were implemented to align model-inferred states with EEG-defined sleep stages. Among the twelve tested pipelines, the …


Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe May 2025

Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe

All Theses

In high-demand environments, the ability to manage cognitive workload can mean the difference between optimal or safe performance and critical failure or accidents. Veterans face an elevated risk of fatal motor vehicle accidents due to post-deployment stress, combat-related injuries, and challenges readjusting to civilian driving. This study explores how cognitive workload affects reaction time performance using a driving simulator by collecting and analyzing subjective workload ratings (using the NASA-TLX survey), physiological signals from eye-tracking and performance data from a sample of 28 Veterans.

We examined how task difficulty, cognitive indicators and personal attributes influence reaction times across an interactive driving …


Kernel Density Estimation And Convolution, Nicholas Tenkorang May 2025

Kernel Density Estimation And Convolution, Nicholas Tenkorang

Open Access Theses & Dissertations

Kernel Density Estimation (KDE) is a widely used technique for estimating the probability density function of a random variable. In this study, we revisit KDE through the lens of convolution and extend this perspective to special cases such as positive, bounded and heavy tailed random variables. Building on this foundation, we propose a novel simulation-based density estimation method that generates new data by adding noise to observed values and then smoothing the resulting histogram using splines. A minor adjustment to natural cubic splines is required to ensure nonnegative estimates. The noise is drawn from a class of bounded polynomial kernel …


Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer May 2025

Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer

Data Science Undergraduate Honors Theses

Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …