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Articles 271 - 300 of 2918
Full-Text Articles in Applied Statistics
Advancement Of Iterative Optimization Technology Algorithms Toward Calibration-Free Process Analytical Technology Applications, Adam Rish
Electronic Theses and Dissertations
The expansion of spectroscopic process analytical technology (PAT) tools within the pharmaceutical industry has the potential to elevate the current state-of-the-art of pharmaceutical manufacturing by offering opportunities for reduced quality testing times, enhanced process control, and greater production flexibility. Spectroscopic PAT tools are dependent on multivariate models to extract the relevant information from the spectral outputs. However, there is a substantial calibration burden for developing and maintaining these multivariate models that discourages the application of PAT, despite the encouragement from regulators. This has led to an interest in calibration-free methods such as iterative optimization technology (IOT) for spectroscopic PAT that …
An Improved Bayesian Pick-The-Winner (Ibpw) Design For Randomized Phase Ii Clinical Trials, Wanni Lei, Maosen Peng, Xi K. Zhou
An Improved Bayesian Pick-The-Winner (Ibpw) Design For Randomized Phase Ii Clinical Trials, Wanni Lei, Maosen Peng, Xi K. Zhou
COBRA Preprint Series
Phase II clinical trials play a pivotal role in drug development by screening a large number of drug candidates to identify those with promising preliminary efficacy for phase III testing. Trial designs that enable efficient decision-making with small sample sizes and early futility stopping while controlling for type I and II errors in hypothesis testing, such as Simon’s two-stage design, are preferred. Randomized multi-arm trials are increasingly used in phase II settings to overcome the limitations associated with using historical controls as the reference. However, how to effectively balance efficiency and accurate decision-making continues to be an important research topic. …
Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger
Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger
Master's Theses
In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …
An Analysis Of Lyrical Repetition And Popularity In Popular Music Genres, Josh White
An Analysis Of Lyrical Repetition And Popularity In Popular Music Genres, Josh White
Undergraduate Honors Capstone Projects
This paper examines the correlation between repetitiveness and popularity in the genres of Christian, Country, EDM, Hip-Hop, Latin, Pop, R&B, and Rock. Repetitiveness is defined by the frequency of repeated words in lyrics, and the average number of streams per day defines popularity. This analysis also acknowledges the "popularity" metric provided by Spotify in calculating the correlation. To calculate this correlation, I wrote a program that accesses the Spotify and Genius APIs to gather metadata related to 76,069 songs from 1,246 artists, including data on repetitiveness, tempo, duration, and Spotify's audio metrics of "danceability," "energy," "speechiness," "acousticness," and "instrumentalness." I …
Efficient Fully Bayesian Approaches To Brain Activity Mapping With Complex-Valued Fmri Data: Analysis Of Real And Imaginary Components In A Cartesian Model And Extension To Magnitude And Phase In A Polar Model, Zhengxin Wang
All Dissertations
Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. Traditional fMRI analyses have largely focused on magnitude information, often overlooking the potential insights offered by phase data, and therefore, lead to underutilization of available data and flawed statistical assumptions. This dissertation proposes two efficient, fully Bayesian approaches for the analysis of complex-valued functional magnetic resonance imaging (cv-fMRI) time series.
Chapter 2 introduces the model, referred to as CV-sSGLMM, using the real and imaginary components of cv-fMRI data and sparse spatial generalized linear mixed model prior. This model extends the …
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Theses and Dissertations
This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.
The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …
Using Probability Theory To Calculate The Odds That Either Candidate Wins The 2024 Presidential Election, Andrew Ruggero
Using Probability Theory To Calculate The Odds That Either Candidate Wins The 2024 Presidential Election, Andrew Ruggero
Department of Applied Mathematics & Statistics Faculty Publications
In the U.S., where the electoral college is used to determine the votes of an election, calculating the odds of a president winning is not as simple as looking at the total vote percentages. With each state not exactly having a proportionally linear amount of votes per its population, the total percentage doesn’t mean much. As such, in order to calculate these odds, we must look at a variety of winning combinations per each candidate. First, we must take into account that swing states are the only ones that matter. Defined as a 5% difference between the two main candidates, …
"Who Wrote The Epistle, God Only Knows": A Statistical Authorial Analysis Of Hebrews In Comparison With Pauline And Lukan Literature, Benjamin J. Erickson
"Who Wrote The Epistle, God Only Knows": A Statistical Authorial Analysis Of Hebrews In Comparison With Pauline And Lukan Literature, Benjamin J. Erickson
Senior Honors Theses
The authorship of Hebrews has been a point of contention for scholars for the past two millennia. While the epistle is traditionally attributed to Paul, many scholars assert that it carries thematic, structural, and stylistic differences from the remainder of his extant epistles; therefore, many other possible authors have been proposed. Of these, only Luke has other New Testament writings. Therefore, this project conducts a statistical comparison of Hebrews to the Pauline and Lukan corpora using stylometric authorial analysis methods. This analysis demonstrates that Hebrews is stylistically closer to Lukan literature than Pauline (but not to a significant degree), and …
Benthic Community Response To The Impacts Of Proposed Sediment Diversions In Louisiana Estuaries, Jillian C. Tupitza
Benthic Community Response To The Impacts Of Proposed Sediment Diversions In Louisiana Estuaries, Jillian C. Tupitza
LSU Doctoral Dissertations
Sediment diversions designed to mitigate land loss in coastal Louisiana will likely cause ecosystem-wide shifts. The first diversion, planned for Barataria Bay, will divert fresh water and sediment from the Mississippi River into the surrounding wetlands to help them keep pace with high rates of relative sea-level rise (RSLR). Estuarine benthic communities were used in this study as tools to characterize ecological patterns in the context of anticipated salinity changes. I reviewed relevant literature, conducted a two-year survey of Barataria Bay benthos, executed a reciprocal transplant experiment to describe changes that might occur in both community composition and trophic dynamics, …
Legal Process Durations In Domestic Violence Cases, Gabrielle Meyers, Jon Anderson
Legal Process Durations In Domestic Violence Cases, Gabrielle Meyers, Jon Anderson
Undergraduate Research Symposium 2024
Slow court case processing is a significant concern, particularly in regard to their adverse implications for survivors of serious crimes such as domestic abuse and sexual assault. This study investigates a number of factors that may influence the duration of court case proceedings using court records from three Minnesota counties. Focusing on cases of domestic violence, sexual assault, kidnapping, harassment, stalking, and various other sex crimes, we employ survival analysis methods to explore the effects of various factors on the duration of court case processing. Our analysis considers the effects of factors such as type of crime, form of legal …
The Relationship Between Fatalities In Police Violence And Their Identifying Characteristics: Age, Gender, Race, And Region, Yuechu Hu
Undergraduate Research Symposium 2024
Police violence, highlighted by the George Floyd incident in 2020, has intensified concerns about police brutality and perceived racism in U.S. law enforcement (AP News, 2022). Therefore, we intend to analyze Fatal Encounters data, which documents non-police deaths that occur in the presence of the police in the United States. By creating statistical tables and graphs, as well as applying time-series methods, classification and regression trees, and a multinomial logistic regression model, we find that males and transgender people are more likely than females to encounter victimization during police brutality enforcement for any cause of death. Victims older than 19 …
Optimizing Nba Roster Construction, Nick R. Riccardi
Optimizing Nba Roster Construction, Nick R. Riccardi
Sport Management - All Scholarship
This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.
Can Compiled Player War Predict Mlb Team Win Percentage?, Thomas Hertel
Can Compiled Player War Predict Mlb Team Win Percentage?, Thomas Hertel
Mathematics Senior Capstone Papers
The baseball statistic Wins Above Replacement (WAR) is a complex yet effective metric for approximating the contribution of a player to his team through representing how many more wins his team ought to earn than with a AAAA player in his stead. The intent of this paper is to test whether the accumulation of player’s WAR can be extended to satisfy another discipline of SABRmetrics, i.e. predicting an entire team’s future performance, through modeling the sum’s correspondence (or lack thereof) to wins. If WAR is shown to extend in this way then franchise front offices could feasibly isolate it as …
Using Multiple Regression Analysis To Determine The Strength Of Certain Factors On Student Absenteeism, Emmitt Antwine
Using Multiple Regression Analysis To Determine The Strength Of Certain Factors On Student Absenteeism, Emmitt Antwine
Mathematics Senior Capstone Papers
During the 2015-16 academic year, approximately 16% of the student population—exceeding 7 million students—were absent from school for 15 days or more. The escalation in chronic absenteeism is influenced by various factors, including poor health conditions, nonstandard work schedules of parents, socioeconomic disadvantages, changes in household compositions, frequent residential relocation, and substantial family responsibilities. Previous research on student absenteeism has examined the negative impacts that chronic absenteeism has had on students in diverse communities such as racial minorities, students with disabilities, and English Language Learners communities. We utilized information obtained from the U.S. Department of Education’s Civil Rights Data Collection …
Factors That Contribute To Completing Gateway Math Course At Southern University, Emma Colvin
Factors That Contribute To Completing Gateway Math Course At Southern University, Emma Colvin
Mathematics Senior Capstone Papers
At Southern University in Shreveport, Louisiana, there are several pathways students can take to complete the institution’s required Gateway Math Courses (GMC). The GMC consists of Math 133, Math 135, and Math 136. Currently, there is a significantly low passing rate for these courses potentially due to several factors such as the student’s math ACT score, the student’s age, whether or not the student took optional developmental math courses beforehand, and whether or not the student took these courses online or in person.
Does The ”Freshman 15” Exist?, Peyton Albritton
Does The ”Freshman 15” Exist?, Peyton Albritton
Mathematics Senior Capstone Papers
This experiment was performed to determine whether the environmental changes of adapting from high school to college impact a student’s weight. Using a Google form, we collected data from 58 college students in two Psychology 102 classes, with ages ranging from seventeen to twenty-two. The students were asked a series of questions regarding their age and gender, as well as their eating, sleeping, and activity habit changes. Data was analyzed using hypothesis testing and a t-test.
Injuries On Artificial Turf Vs. Natural Grass In The Nfl, Robert Emory
Injuries On Artificial Turf Vs. Natural Grass In The Nfl, Robert Emory
Mathematics Senior Capstone Papers
The purpose of this research is to determine if artificial turf causes more injuries than natural grass. By referencing different statistics from a sample of games from the 2023 National Football League season. Out of the ten games sampled, five were played on natural grass and five were played on artificial turf. We ran the data collected from these games through two different regression analysis models that output p-values to show what truly caused the injuries. Our model uses a player’s position, height, weight, age, and snap counts along with the field surface type to see how if an injury …
Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng
Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng
Journal of Food and Drug Analysis
In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection system (import food inspection (IFI) system) to select batches via a random sampling method to manage the risk levels of various food products complying with regulatory inspection procedures. Several countries have implemented artificial intelligence (AI) technology to improve domestic governmental processes, social service, and public feedback. AI technologies are applied in border inspection by the Taiwan Food and Drug Administration (TFDA). Risk management of border inspections …
Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman
Forecasting Stock Prices Using Arima Models And Technical Analysis, Muath I. Almaiman
Theses and Dissertations
This thesis explores the integration of Autoregressive Integrated Moving Average (ARIMA) models and technical analysis to forecast stock prices, with a focus on Coca-Cola's (KO) and Netflix’s (NFLX) stocks. It examines the effectiveness of combining ARIMA models, known for their predictive accuracy in time-series analysis, with technical indicators, particularly moving averages. The study evaluates whether this integrated approach can enhance the predictive capability of stocks prices beyond traditional methods. The predictive capability is evaluated using error metrics from the ARIMA models, as well as by assessing the return earned using simple rules based on the technical indicators. Utilizing data spanning …
Session 6: The Size-Biased Lognormal Mixture With The Entropy Regularized Algorithm, Tatjana Miljkovic, Taehan Bae
Session 6: The Size-Biased Lognormal Mixture With The Entropy Regularized Algorithm, Tatjana Miljkovic, Taehan Bae
SDSU Data Science Symposium
A size-biased left-truncated Lognormal (SB-ltLN) mixture is proposed as a robust alternative to the Erlang mixture for modeling left-truncated insurance losses with a heavy tail. The weak denseness property of the weighted Lognormal mixture is studied along with the tail behavior. Explicit analytical solutions are derived for moments and Tail Value at Risk based on the proposed model. An extension of the regularized expectation–maximization (REM) algorithm with Shannon's entropy weights (ewREM) is introduced for parameter estimation and variability assessment. The left-truncated internal fraud data set from the Operational Riskdata eXchange is used to illustrate applications of the proposed model. Finally, …
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
Session 6: Model-Based Clustering Analysis On The Spatial-Temporal And Intensity Patterns Of Tornadoes, Yana Melnykov, Yingying Zhang, Rong Zheng
SDSU Data Science Symposium
Tornadoes are one of the nature’s most violent windstorms that can occur all over the world except Antarctica. Previous scientific efforts were spent on studying this nature hazard from facets such as: genesis, dynamics, detection, forecasting, warning, measuring, and assessing. While we want to model the tornado datasets by using modern sophisticated statistical and computational techniques. The goal of the paper is developing novel finite mixture models and performing clustering analysis on the spatial-temporal and intensity patterns of the tornadoes. To analyze the tornado dataset, we firstly try a Gaussian distribution with the mean vector and variance-covariance matrix represented as …
A Causal Inference Approach For Spike Train Interactions, Zach Saccomano
A Causal Inference Approach For Spike Train Interactions, Zach Saccomano
Dissertations, Theses, and Capstone Projects
Since the 1960s, neuroscientists have worked on the problem of estimating synaptic properties, such as connectivity and strength, from simultaneously recorded spike trains. Recent years have seen renewed interest in the problem coinciding with rapid advances in experimental technologies, including an approximate exponential increase in the number of neurons that can be recorded in parallel and perturbation techniques such as optogenetics that can be used to calibrate and validate causal hypotheses about functional connectivity. This thesis presents a mathematical examination of synaptic inference from two perspectives: (1) using in vivo data and biophysical models, we ask in what cases the …
Sparse Bayesian Variable Selection In High‐Dimensional Logistic Regression Models With Correlated Priors, Zhuanzhuan Ma, Zifei Han, Souparno Ghosh, Liucang Wu, Min Wang
Sparse Bayesian Variable Selection In High‐Dimensional Logistic Regression Models With Correlated Priors, Zhuanzhuan Ma, Zifei Han, Souparno Ghosh, Liucang Wu, Min Wang
School of Mathematical & Statistical Sciences Faculty Publications
In this paper, we propose a sparse Bayesian procedure with global and local(GL) shrinkage priors for the problems of variable selection and classification in high-dimensional logistic regression models. In particular, we consider two types of GL shrinkage priors for the regression coefficients, the horseshoe (HS)prior and the normal-gamma (NG) prior, and then specify a correlated prior for the binary vector to distinguish models with the same size. The GL priors are then combined with mixture representations of logistic distribution to construct a hierarchical Bayes model that allows efficient implementation of a Markov chain Monte Carlo (MCMC) to generate samples from …
An Analysis Of Corporate Social Responsibility And Real Earnings Management, Rachel Brassine
An Analysis Of Corporate Social Responsibility And Real Earnings Management, Rachel Brassine
Theses, Dissertations and Capstones
Real earnings management (REM) is costly in the form of intense loan restrictions, increased interest expense, and public scrutiny. Nevertheless, companies still practice REM. Based on agency and stakeholder theories, this research predicts that as a company’s CSR score increases, REM will decrease, and this association will become more negative when a critical mass of females on the board of directors exists and when a board-level CSR committee is present. This study also predicts that when a company offers an executive incentive plan based on CSR metrics, REM will decrease, and the relationship will become more negative with a critical …
Es/Ph/Sra 511: Applied Statistics, Minsoo Kang
Es/Ph/Sra 511: Applied Statistics, Minsoo Kang
GMAS Course Syllabi
No abstract provided.
Understanding Social Dynamics In Toxic Conversations And Public Health Intervention Acceptance On Social Media, Ana Aleksandric
Understanding Social Dynamics In Toxic Conversations And Public Health Intervention Acceptance On Social Media, Ana Aleksandric
Computer Science and Engineering Dissertations - Archive
Social media is now central to daily life, offering users a space to share content and opinions. However, these platforms also facilitate the spread of hate speech and misinformation, which can negatively impact public health. This dissertation develops methodologies to analyze social media data for insights that could inform health interventions. The research first examines user responses to toxic content, focusing on behavioral and emotional reactions, as well as group dynamics and bystander effects in toxic interactions. Another key focus is public opinion toward health interventions, particularly COVID-19 vaccination, using geolocated posts and analyzing factors such as race, ethnicity, and …
Exact Testing For Heteroscedasticity In A Two-Way Layout In Variety Frost Trials When Incorporating A Covariate, Angelika A. Pilkington, Brenton R. Clarke, Dean A. Diepeveen
Exact Testing For Heteroscedasticity In A Two-Way Layout In Variety Frost Trials When Incorporating A Covariate, Angelika A. Pilkington, Brenton R. Clarke, Dean A. Diepeveen
Grain and Other Field Crops Research Articles
Two-way layouts are common in grain industry research where it is often the case that there are one or more covariates. It is widely recognised that when estimating fixed effect parameters, one should also examine for possible extra error variance structure. An exact test for heteroscedasticity, when there is a covariate, is illustrated for a data set from frost trials in Western Australia. While the general algebra for the test is known, albeit in past literature, there are computational aspects of implementing the test for the two way when there are covariates. In this scenario the test is shown to …
Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe
Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe
Data Science and Data Mining
This project estimates a regression model to predict the superconducting critical temperature based on variables extracted from the superconductor’s chemical formula. The regression model along with the stepwise variable selection gives a reasonable and good predictive model with a lower prediction error (MSE). Variables extracted based on atomic radius, valence, atomic mass and thermal conductivity appeared to have the most contribution to the predictive model.
A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci
A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci
Theses and Dissertations--Civil Engineering
Researchers and practitioners studied the effects ride-hailing had in cities before the covid-19 pandemic. Previous research found ride-hailing to produce negative externalities, such as reducing transit ridership and increasing congestion in various cities. Since the pandemic, ride-hailing ridership has nearly recovered to pre-pandemic levels in Chicago. Ride-hailing ridership has grown steadily since the pandemic while a rider’s willingness to share their trip stagnated. Ride-hailing ridership nearly recovering to pre-covid levels in Chicago suggests that transportation planners, and policy makers, will need to continue assessing the impacts ride-hailing trips have in their cities.
Pickup and drop off locations in the Chicago …
Judging Our New Judges: Why We Must Remove Artificial Intelligence From Our Courtrooms Now, Kieran Duffy Newcomb
Judging Our New Judges: Why We Must Remove Artificial Intelligence From Our Courtrooms Now, Kieran Duffy Newcomb
Honors Theses and Capstones
In this paper, I explore some of the ways in which artificial intelligence might enhance the sentencing process through recidivism prediction technology. Notably, this technology can increase the accuracy of risk predictions and the speed with which sentencing decisions are reached. I then show, however, that the recidivism prediction technology is likely to turn into what data scientist Cathy O’Neil calls a Weapon of Math Destruction. The potential harmfulness of this technology is due not to the inherent nature of the technology, but the symbiotic relationship it will have with our already harmful criminal justice system. I argue that the …