Statistics and Probability Commons^™

Markov Model Composition Of Balinese Reyong Norot Improvisations, Taylor Flanagan, Robert Rovetti

Honors Thesis

Markov models are mathematical structures that model the transition between possible states based on the probability of moving from one state to any other. Thus, given a distribution of starting points, the model produces a chain of states that are visited in sequence. Such models have been used extensively to generate music based on probabilities, as sequences of states can represent sequences of notes and rhythms. While music generation is a common application of Markov models, most existing work attempts to reconstruct the musical style of classical Western composers. In this thesis, we produce a series of Markov chains that …

Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh

Publications and Research

Brownian Motion which is also considered to be a Wiener process and can be thought of as a random walk. In our project we had briefly discussed the fluctuations of financial indices and related it to Brownian Motion and the modeling of Stock prices.

Cardiovascular Complications Of Systemic Lupus Erythematosus: Impact Of Risk Factors And Therapeutic Efficacy--A Tertiary Centre Experience In An Appalachian State, Elise Danielle Mcveigh, Amna Batool, Arnold J. Stromberg, Ahmed K. Abdel-Latif, Nayef Mohammed Kazzaz

Statistics Faculty Publications

OBJECTIVES: Cardiovascular complications became a notable cause of morbidity and mortality in patients with lupus as therapeutic advancements became more efficient at managing other complications. The Appalachian community in Kentucky has a higher prevalence of traditional cardiovascular risk factors, predisposing them to cardiovascular events. Namely, the mean body mass index of the members of the Kentucky Appalachian community was reported at 33 kg/m² and 94.3% of male members of this community use tobacco. We sought to identify risk factors that predispose patients with lupus to cardiovascular morbidities and examine the effect of immunomodulatory drugs.

METHODS: We identified 20 UKHS …

Confidence Intervals Of Covid-19 Vaccine Efficacy Rates, Frank Wang

Numeracy

This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework. Under the classical approach, there is no probability associated with a parameter, and the meaning of confidence intervals can be misconstrued by inexperienced students. With Bayesian statistics, one can find the posterior probability distribution of an unknown parameter, and state the probability of vaccine efficacy rate, which makes the communication of uncertainty more flexible. We use a hypothetical example and a real baseball example to guide readers to …

Species In Vernal Pools: Anova, Lisa Manne

Open Educational Resources

A one-way analysis of variance exercise using data on species diversities from vernal pools.Data are from vernal pools in Willowbrook Park (adjacent to College of Staten Island's campus) in spring.

The typical ANOVA gives a straightforward result (significant anova, easily-interpreted Tukey-Kramer analysis). This data set requires more nuanced interpretation, as the ANOVA is marginally significant, and Tukey-Kramer yields one significant pairwise comparison between groups. Relative lack of variation within groups explains this apparent enigma.

Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri

Computer Science and Computer Engineering Undergraduate Honors Theses

In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been …

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing …

Retail Trading And Stock Volatility: The Case Of Robinhood, Cooper Jones

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

We examine the relation between Robinhood usership and stock market volatility. We show that daily fluctuations in Robinhood usership, which is used to proxy retail trading, significantly influence various measures of volatility. These results might suggest that Robinhood users contribute to noise trading as they are generally individuals trading on name recognition, media coverage, popularity, and familiarity of products, rather than on fundamental values. In our empirical approach, we find that the percentage increase in Robinhood usership Granger causes increases in daily stock volatility.

Randomised Trials At The Level Of The Individual, Jay J H. Park, Nathan Ford, Denis Xavier, Per Ashorn, Rebecca F. Grais, Zulfiqar Ahmed Bhutta, Herman Goossens, Kristian Thorlund, Maria Eugenia Socias, Edward J. Mills

Centre of Excellence in Women and Child Health

In global health research, short-term, small-scale clinical trials with fixed, two-arm trial designs that generally do not allow for major changes throughout the trial are the most common study design. Building on the introductory paper of this Series, this paper discusses data-driven approaches to clinical trial research across several adaptive trial designs, as well as the master protocol framework that can help to harmonise clinical trial research efforts in global health research. We provide a general framework for more efficient trial research, and we discuss the importance of considering different study designs in the planning stage with statistical simulations. We …

Improving Access And Health Outcomes Through Carepartners And Medaccess Programs, Elora Way, Becky Wurwarg

Publications

Access to Care, a division of MaineHealth, works to ensure that Maine residents have access to comprehensive and affordable healthcare that improves community wellbeing. In 2020, as part of its ongoing commitment to evaluating the effectiveness of its programs, Access to Care partnered with the University of Southern Maine’s Data Innovation Project to conduct a multi-year retrospective evaluation of its two longest-running initiatives, CarePartners and MedAccess. Established in 2001, CarePartners coordinates donated healthcare services for low-income, uninsured residents across six Maine counties by connecting participants with case managers, primary care providers, and pharmacy benefits. Between 2016 and 2019, 4,426 individuals …

Applications Of Evidence Theory To High-Consequence Systems Safety, Christina Marie Deffenbaugh

Mathematics & Statistics ETDs

Issues linked to abnormal environments (like high-consequence systems safety, e.g., nuclear weapon components, bridges, apartment buildings, etc.) may have insufficient information to use either classical statistical methods or Bayesian approaches for calculating associated probabilistic risks, so there is often a requirement for another method that can deal with a low-information situation to obtain a risk assessment. Belief/plausibility measures of uncertainty from A. P. Dempster and G. Shafer’s Evidence Theory is one such method. This thesis has two goals. First, a brief discussion on belief/plausibility measures as an application of Evidence Theory will familiarize the audience with its history and how …

Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn

Finance Undergraduate Honors Theses

When talking about financial instruments correlation is often thrown around as a measure of the relation between two securities. An often more useful or tradeable measure is cointegration. Cointegration is the measure of two securities tendency to revert to an average price over time. In other words, cointegration ignores directionality and only cares about the distance between two securities. For a mean reversion strategy such as statistical arbitrage cointegration proves to be a far more reliable statistical measure of mean reversion, and while it is more reliable than correlation it still has its own problems. One thing to consider is …

The Hybridizing Ions Treatment (Hit) Method Development And Computational Study On Sars-Cov-2 E Protein., Shengjie Sun

Open Access Theses & Dissertations

Fast and accurate calculations of the electrostatic features for highly charged biomolecules such as DNA, RNA, highly charged proteins, are crucial but challenging tasks. Traditional implicit solvent methods calculate the electrostatic features fast, but they are not able to balance the high net charges in the biomolecules effectively. Explicit solvent methods add unbalanced ions to neutralize the highly charged biomolecules in molecular dynamic simulations, which require more expensive computing resources. Here we developed a novel method, the Hybridizing Ions Treatment (HIT) method, which hybridizes the implicit solvent method with the explicit method to realistically calculate the electrostatic potential for highly …

Robust Variable Selection In Multiple Linear Regression Via Penalized Least Trimmed Squares., Reagan Kesseku

Open Access Theses & Dissertations

Variable selection has been studied using different approaches. Its growing importance lies in numerous applications to high-dimensional data from experiments and natural phenomena. Often, models are to be constructed from such data based on significant variables for estimation or prediction purposes. This demands not just any variable selectionmethod, but one that is robust, computationally efficient and with other desirable statistical properties. Besides the high-dimensionality of such data, the presence of outliers is common due to heterogeneous sources. Though outliers often contain useful information, they can unduly influence non-robust estimators to produce misleading results. This is the case for ordinary least …

Estimating Cumulative Incidence Rate On Interval Censored Data In An Illness-Death Model., Chen Qian

Electronic Theses and Dissertations

Phase IV clinical trials are designed to monitor long-term side effects caused overtime by the medical treatment. For instance, in advanced primary cancer treatment, childhood cancer survivors are often at risk of developing undesired events, such as cardiotoxicity, during their adulthood. Such problems could be due to their cancer or the treatment they received for their cancer such as radiation or intensive chemotherapy. Cardiotoxicity can be diagnosed with electrophysiology with measurements of fraction shortening, afterload, etc. Often the primary focus of a study could be on estimating the cumulative incidence of a particular outcome of interest such as cardiotoxicity. However, …

Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll

Electronic Theses and Dissertations

The use of group testing to identify individuals with targeted outcomes in a population can greatly improve the efficiency, speed, and cost effectiveness of testing a population for an outcome, or at least for identifying the prevalence of an outcome in a population. The implementation of causal inference techniques can provide the basis for an observational study that would allow an investigator to gather estimates for treatment effectiveness if group testing was conducted on the population in a certain way. This thesis examines a simulation of the above outlined principles in order to demonstrate a potential application for determining treatment …

A Data Adaptive Model For Retail Sales Of Electricity, Johanna Marcelia

Boise State University Theses and Dissertations

When fitting a model to a data set, the goal is to create a model that captures the trends present in the data. However, data often contains regions where the underlying model changes or exhibits shifts in certain parameters due to economic events. These locations in the data are known as changepoints, and ignoring them can result in high error and incorrect forecasts. By developing a specific cost function and optimizing using the genetic algorithm, we are able to locate and account for the changepoints in a given data set. We specifically apply this process to the retail sales of …

Food Insecurity And Adiposity Among Children And Adults Nhanes 2015-2016, Denise Vidal

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background: Obesity is a preventable disease that has been associated with many adverse health outcomes. A possible factor that may influence adiposity development is food insecurity. Although several epidemiological studies have been conducted examining the association between food insecurity and adiposity among children and adults, results have been inconsistent. Objective: This cross-sectional study investigates the relationship between food insecurity and adiposity among children and adults using recent data from a representative sample of the US population. Methods: We examined 3,391 adults and 2,837 children from the National Health and Nutrition Examination Survey (NHANES) 2015-2016. Household food insecurity was assessed using …

Joint Spacing In The Caples Lake Granodiorite Of The Sierra Nevada Batholith In Eldorado National Forest, California: A Comparative Analysis Of Joint Sets And Data Resolution, Jimmy Wood

Theses/Capstones/Creative Projects

Joints are the most common deformation structure in the Earth’s upper crust and exert a significant influence on structural stability, landscape morphology, and fluid flow . Therefore, a greater understanding of fracture parameters (e.g., length, aperture, etc.) allows us to more accurately predict their presence, persistence, and prevalence, in the subsurface . We study the fracture spacing of two sub-orthogonal joint sets—66 NE-246 SW and 330 NW-150 SE—in the Caples Lake granodiorite of the Sierra Nevada Batholith, California. Specifically, we investigate 1) their spacing distributions with a keen interest in power-law (fractal) spacing, 2) distribution comparisons between master and cross …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations and Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …