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Articles 1 - 30 of 3439
Full-Text Articles in Physical Sciences and Mathematics
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Biology and Medicine Through Mathematics Conference
No abstract provided.
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. …
A Novel Correction For The Multivariate Ljung-Box Test, Minhao Huang
A Novel Correction For The Multivariate Ljung-Box Test, Minhao Huang
Computational and Data Sciences (PhD) Dissertations
This research introduces an analytical improvement to the Multivariate Ljung-Box test that addresses significant deviations of the original test from the nominal Type I error rates under almost all scenarios. Prior attempts to mitigate this issue have been directed at modification of the test statistics or correction of the test distribution to achieve precise results in finite samples. In previous studies, focused on designing corrections to the univariate Ljung-Box, a method that specifically adjusts the test rejection region has been the most successful of attaining the best Type I error rates. We adopt the same approach for the more complex, …
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 …
"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 …
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 …
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 …
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 …
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 …
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, …
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 …
Statistical Consulting In Academia: A Review, Ke Xiao
Statistical Consulting In Academia: A Review, Ke Xiao
Major Papers
This paper reviews the state of statistical consulting in academia by performing a literature review on this topic in chapters 1 and 2. Chapter 1 overviews general aspects of statistical consulting and types of centers that conduct such services in academia. In Chapter 2 we summarise the literature about the common logistics and processes for conducting statistical consulting in academia. In Chapters 3 and 4, we analyze data on statistical consulting centers for the largest 100 universities in the USA. We also review the literature on the future of statistical consulting in academia in the era of big data and …
Formulating An Efficient Statistical Test Using The Goodness Of Fit Approach With Applications To Real-Life Data, S. A. Qaid, S. E. Abo Youssef Prof., Mahmoud Mansour
Formulating An Efficient Statistical Test Using The Goodness Of Fit Approach With Applications To Real-Life Data, S. A. Qaid, S. E. Abo Youssef Prof., Mahmoud Mansour
Basic Science Engineering
Statistical tests are very important for researchers to make decisions. In particular, when the tests are non-parametric, they are of greater importance because they can be applied to a wide range of data sets regardless of knowing the distribution of these data. Researchers are therefore racing to obtain efficient tests for making good decisions based on the results of these tests. In this study, NBU (2)L was used based on the goodness of fit approach to present an efficient statistical test. The efficiency of the proposed test was computed, and the results were compared to those of other tests. Critical …
Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe
Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe
Data Science and Data Mining
Cyberbullying refers to the act of bullying using electronic means and the internet. In recent years, this act has been identifed to be a major problem among young people and even adults. It can negatively impact one’s emotions and lead to adverse outcomes like depression, anxiety, harassment, and suicide, among others. This has led to the need to employ machine learning techniques to automatically detect cyberbullying and prevent them on various social media platforms. In this study, we want to analyze the combination of some Natural Language Processing (NLP) algorithms (such as Bag-of-Words and TFIDF) with some popular machine learning …
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.
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen
Theses and Dissertations (Comprehensive)
The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …
Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner
Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner
Dissertations, Master's Theses and Master's Reports
The unifying theme of this thesis is the characterization of “perfect randomness,” i.e., independent and identically distributed (IID) stochastic processes as these are applied in physical science. Two specific and mathematically distinct applications are chosen: (i) Radar and optical polarimetry; (ii) Analysis of time series in meteorology. In (i), IID process of a special kind, namely, with a distribution defined by symmetry, is used to link its multivariate Gaussian density to uniformity on the Poincaré sphere. This “statistical ellipsometry” approach is then used to relate polarimetric mismatches or imbalances to ellipsometric variables and suitably chosen cross-correlation measures. In (ii), recently …
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 …
Classification In Supervised Statistical Learning With The New Weighted Newton-Raphson Method, Toma Debnath
Classification In Supervised Statistical Learning With The New Weighted Newton-Raphson Method, Toma Debnath
Electronic Theses and Dissertations
In this thesis, the Weighted Newton-Raphson Method (WNRM), an innovative optimization technique, is introduced in statistical supervised learning for categorization and applied to a diabetes predictive model, to find maximum likelihood estimates. The iterative optimization method solves nonlinear systems of equations with singular Jacobian matrices and is a modification of the ordinary Newton-Raphson algorithm. The quadratic convergence of the WNRM, and high efficiency for optimizing nonlinear likelihood functions, whenever singularity in the Jacobians occur allow for an easy inclusion to classical categorization and generalized linear models such as the Logistic Regression model in supervised learning. The WNRM is thoroughly investigated …
The Distribution Of The Significance Level, Paul O. Monnu
The Distribution Of The Significance Level, Paul O. Monnu
Electronic Theses and Dissertations
Reporting the p-value is customary when conducting a test of hypothesis or significance. The likelihood of getting a fictitious second sample and presuming the null hypothesis is correct is the p-value. The significance level is a statistic that interests us to investigate. Being a statistic, it has a distribution. For the F-test in a one-way ANOVA and the t-tests for population means, we define the significance level, its observed value, and the observed significance level. It is possible to derive the significance level distribution. The t-test and the F-test are not without controversy. Specifically, we demonstrate that as sample size …
Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan
Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan
Journal of Environmental Science and Sustainable Development
Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
SMU Data Science Review
Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …
Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre
Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre
SMU Data Science Review
Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …
Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin
Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin
Introduction to Research Methods RSCH 202
This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …
The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion, Grace Y. Ng, Ritesh Karsalia, Ryan S. Gallagher, Austin J. Borja, Jianbo Na, Scott Mcclintock, Neil R. Malhotra
The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion, Grace Y. Ng, Ritesh Karsalia, Ryan S. Gallagher, Austin J. Borja, Jianbo Na, Scott Mcclintock, Neil R. Malhotra
Mathematics Faculty Publications
INTRODUCTION: The relationship between socioeconomic status and neurosurgical outcomes has been investigated with respect to insurance status or median household income, but few studies have considered more comprehensive measures of socioeconomic status. This study examines the relationship between Area Deprivation Index (ADI), a comprehensive measure of neighborhood socioeconomic disadvantage, and short-term postoperative outcomes after lumbar fusion surgery. METHODS: 1861 adult patients undergoing single-level, posterior-only lumbar fusion at a single, multihospital academic medical center were retrospectively enrolled. An ADI matching protocol was used to identify each patient's 9-digit zip code and the zip code-associated ADI data. Primary outcomes included 30- and …
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown
Graduate Theses and Dissertations
Single case research design (SCRD) is a common methodology used across clinical disciplines to determine treatments effectiveness by comparing treatment conditions to baseline conditions in individual cases, usually among researchers working with smaller samples. Although popular within behavioral disciplines such as special education and behavioral analysis, studies have begun to emerge in counseling. However, guidance and current understanding of the use of SCRD in counseling is limited. A content analysis of counseling journals from 2003 to 2014 yielded only 7 studies using SCRD. In 2015, the flagship counseling journal, Journal of Counseling and Development, published a special issue on the …
Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas
Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas
Graduate Theses and Dissertations
Over the last several decades, plastic waste has gradually accumulated while slowly degrading in terrestrial and oceanic environments. Recently, there has been an increased effort to identify the possible sources of plastic to understand how they affect vulnerable beaches. This issue is of particular concern in the Gulf of Mexico due to the presence of oil, natural gas, and plastic production. In this thesis, we expand upon existing Bayesian plastic attribution models and develop a rigorous statistical framework to map observed beached microplastics to their sources. Within this framework, we combine Lagrangian backtracking simulations of floating particles using nurdle beaching …
Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu
Parameter Estimation For Patient Enrollment In Clinical Trials, Junyan Liu
Undergraduate Honors Theses
In this paper, we study the Poisson-gamma model for recruitment time in clinical trials. We proved several properties of this model that match our intuitions from a reliability perspective, did simulations on this model, and used different optimization methods to estimate the parameters. Although the behaviors of the optimization methods were unfavorable and unstable, we identified certain conditions and provided potential explanations for this phenomenon and further insights into the Poisson-gamma model.
Comparative Analysis Of Teacher Effects Parameters In Models Used For Assessing School Effectiveness: Value-Added Models & Persistence, Merlin J. Kamgue
Comparative Analysis Of Teacher Effects Parameters In Models Used For Assessing School Effectiveness: Value-Added Models & Persistence, Merlin J. Kamgue
Graduate Theses and Dissertations
Longitudinal measures for students have become increasingly popular to estimate the effects of individual teachers and schools. Value-added models are one of the approaches using longitudinal data to evaluate teachers and schools. In the value-added model (VAM) literature, many statistical approaches have been developed and used to estimate teacher or school effects on student learning. This study opted to use a Bayesian multivariate model for evaluating teacher effects. The generalized persistence models can handle longitudinal data, not vertically scaled, allowing for a below-par teacher’s effects correlation across test administrations. This study first generated longitudinal students’ test score data and used …