Multivariate Analysis Commons^™

The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith

Pomona Faculty Publications and Research

Principal components regression (PCR) reduces a large number of explanatory variables down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.

Innate Immunity, The Hepatic Extracellular Matrix, And Liver Injury: Mathematical Modeling Of Metastatic Potential And Tumor Development In Alcoholic Liver Disease., Shanice V. Hudson

Electronic Theses and Dissertations

The overarching goals of the current work are to fill key gaps in the current understanding of alcohol consumption and the risk of metastasis to the liver. Considering the evidence this research group has compiled confirming that the hepatic matrisome responds dynamically to injury, an altered extracellular matrix (ECM) profile appears to be a key feature of pre-fibrotic inflammatory injury in the liver. This group has demonstrated that the hepatic ECM responds dynamically to alcohol exposure, in particular, sensitizing the liver to LPS-induced inflammatory damage. Although the study of alcohol in its role as a contributing factor to oncogenesis and …

Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati

LSU Master's Theses

The spherical metal particles produced from the centrifugal atomization process have been the topic of numerous theoretical, experimental and numerical studies from the past few years. This atomization process uses centrifugal force to break-up molten material into spherical droplets, which are quenched into solidified granules by the flow of cold air on the spherical droplets. In the present work, a transient three-dimensional multiphase CFD model is applied to three different materials: Molten slag, aqueous glycerol solution, and molten Ni-Nb to study the influence of the dimensionless parameters on the centrifugal atomization outcome.

Results from numerical experiments indicated that the droplet …

Identifying Key Factors Associated With High Risk Asthma Patients To Reduce The Cost Of Health Resources Utilization, Amani Ahmad

LSU Master's Theses

Asthma is associated with frequent use of primary health services and places a burden on the United States economy. Identifying key factors associated with increased cost of asthma is an essential step to improve practices of asthma management.

The aim of this study was to identify factors associated with over utilization of primary health services and increased cost via claims data and to explore the effectiveness of case management program in reducing overall asthma related cost.

Claims data analysis for Medicaid insured asthma patients in Louisiana was conducted. Asthma patients were identified using their ICD-9 and ICD-10 codes, forward variable …

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …

Scale-Invariant Geometric Data Analysis (Sigda), Marina Girgis, Max Robinson

STAR Program Research Presentations

The purpose of this research is to introduce a new data analysis method called Scale Invariant Geometric Data Analysis (SIGDA). SIGDA has been shown to be more informative than more common data analysis methods, such as Principal Component Analysis (PCA). SIGDA is used to visualize complex data sets in a way that accurately preserves data patterns and behavior. SIGDA is designed to preserve relative ratios in a numerical matrix, and the number of entries has to be more than the total number of rows and columns. Our research involved providing a simple explanation of SIGDA's mathematical process—simple enough for the …

Pretrial Release And Failure-To-Appear In Mclean County, Il, Jonathan Monsma

Student Research – Stevenson Center

Actuarial risk assessment tools increasingly have been employed in jurisdictions across the U.S. to assist courts in the decision of whether someone charged with a crime should be detained or released prior to their trial. These tools should be continually monitored and researched by independent 3^rd parties to ensure that these powerful tools are being administered properly and used in the most proficient way as to provide socially optimal results. McLean County, Illinois began using the Public Safety Assessment-Court^TM (PSA-Court or simply PSA) risk assessment tool beginning in 2016. This study culls data from the McLean County Jail …

Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

Biology and Medicine Through Mathematics Conference

No abstract provided.

A 3d Characteristics Database Of Land Engraved Areas With Known Subclass, Entni Lin

Student Theses

Subclass characteristics on bullets may mislead firearm examiners when they rely on traditional 2D images. In order to provide indelible examples for training and help avoid identification errors, 3D topography surface maps and statistical methods of pattern recognition are applied to toolmarks on bullets containing known subclass characteristics. This research was conducted by collecting 3D topography surface map data from land engraved areas of bullets fired through known barrels. This data was processed and used to train the statistical algorithms to predict their origin. The results from the algorithm are compared with the “right answers” (i.e. correct IDs) of the …

Designing A Calibration Set In Spectral Space For Efficient Development Of An Nir Method For Tablet Analysis, Md Anik Alam

Electronic Theses and Dissertations

Designing a calibration set is the first step in developing a spectroscopic calibration method for quantitative analysis of pharmaceutical tablets. This step is critical because successful model development depends on the suitability of the calibration data. For spectroscopic-based methods, traditional concentration based techniques for designing calibration sets are prone to have redundant information while simultaneously lacking necessary information for a successful calibration model. The traditional method also follows the same design approach for different spectroscopic techniques and different formulations, thereby lacks the optimizing capability to be technique and formulation specific.

A method for designing a calibration set in the Near …

Fast Identification Of Components Commonly Used In Homemade Explosives By Spectroscopic And Chemometric Methods, Deidre Day Vandenbos, Huggins Msimanga, Christopher Dockery

Master of Science in Chemical Sciences Theses

Homemade explosives (HMEs) have become a global pandemic. This forensic research focuses on developing identification methods that can provide quick, cost effective, non-destructive analysis using portable instrumentation. These capabilities would be invaluable to first responders, military, and security officials to establish an evidentiary link between a suspect and a reference in cases of HMEs, IEDs, arson and environmental contamination.

Modern methods for quick identification of the fuels and oxidant sources used in manufacturing HMEs, include Fourier Transform Infrared (FT-IR) and Raman spectroscopy. Visual confirmation alone, however, is not strong enough to discriminate chemicals with nearly identical spectra, which occurs when …

Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, Ian D. Campbell

Undergraduate Theses and Capstone Projects

To the outside observer, soccer is chaotic with no given pattern or scheme to follow, a random conglomeration of passes and shots that go on for 90 minutes. Yet, what if there was a pattern to the chaos, or a way to describe the events that occur in the game quantifiably. Sports statistics is a critical part of baseball and a variety of other of today’s sports, but we see very little statistics and data analysis done on soccer. Of this research, there has been looks into the effect of possession time on the outcome of a game, the difference …

Chemical And Statistical Analysis Of Karst Groundwater Basin Signatures - Springfield, Mo, Benjamin E. Lockwood

Graduate Theses/Dissertations

Springfield, MO is located on the Springfield Plateau physiographic province. The Springfield plateau contains a number of Mississippian aged units and is mainly capped by the Burlington-Keokuk Formation. The Burlington-Keokuk is a highly fossiliferous limestone with nodular and interbedded chert. Beneath the Burlington-Keokuk lies the Elsey, Reeds Spring, and Pierson Formations respectively which comprise the Springfield Plateau aquifer hydrostratigraphic unit. Within the Springfield Plateau aquifer, a well-developed karst system includes springs, sinkholes, and caves. The Springfield Plateau aquifer is the predominant source for springs and seeps in the Springfield area. The purpose of this study was to understand the differences …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Initial Evidence Of Construct Validity Of Data From A Self-Assessment Instrument Of Technological Pedagogical Content Knowledge (Tpack) In 2-Year Public College Faculty In Texas, Kristin C. Scott

Human Resource Development Theses and Dissertations

Technological pedagogical content knowledge (TPACK) has been studied in K-12 faculty in the U.S. and around the world using survey methodology. Very few studies of TPACK in post-secondary faculty have been conducted and no peer-reviewed studies in U.S. post-secondary faculty have been published to date. The present study is the first reliability and validity of data from a TPACK survey to be conducted with a large sample of U.S. post-secondary faculty. The professorate of 2-year public college faculty in Texas will help their institutions meet the goals of the state’s higher education strategic plan, 60x30TX. In order to do …

Using Random Forests To Describe Equity In Higher Education: A Critical Quantitative Analysis Of Utah’S Postsecondary Pipelines, Tyler Mcdaniel

Butler Journal of Undergraduate Research

The following work examines the Random Forest (RF) algorithm as a tool for predicting student outcomes and interrogating the equity of postsecondary education pipelines. The RF model, created using longitudinal data of 41,303 students from Utah's 2008 high school graduation cohort, is compared to logistic and linear models, which are commonly used to predict college access and success. Substantially, this work finds High School GPA to be the best predictor of postsecondary GPA, whereas commonly used ACT and AP test scores are not nearly as important. Each model identified several demographic disparities in higher education access, most significantly the effects …

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books Collection

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling …

Building A Better Risk Prevention Model, Steven Hornyak

National Youth Advocacy & Resilience Conference

This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.

A Preliminary Study Of Smithport Plain Bottle Morphology In The Southern Caddo Area, Robert Z. Selden Jr.

CRHR: Archaeology

This study expands upon a previous analysis of the Clarence H. Webb collection, which resulted in the identification of two discrete shapes used in the manufacture of the base and body of Smithport Plain bottles. The sample includes the Smithport Plain bottles from the Webb collection, and four new bottles: two previously repatriated specimens in the Pohler Collection, and two from the Mitchell site (41BW4) to test whether those specimens align morphologically with the Belcher Mound or Smithport Landing specimens. Results indicate significant allometry and a significant difference in Smithport Plain body and base shapes for bottles produced at the …

Effect Of Socioeconomic And Demographic Factors On Kentucky Crashes, Aaron Berry Cambron

Theses and Dissertations--Civil Engineering

The goal of this research was to examine the potential predictive ability of socioeconomic and demographic data for drivers on Kentucky crash occurrence. Identifying unique background characteristics of at-fault drivers that contribute to crash rates and crash severity may lead to improved and more specific interventions to reduce the negative impacts of motor vehicle crashes. The driver-residence zip code was used as a spatial unit to connect five years of Kentucky crash data with socioeconomic factors from the U.S. Census, such as income, employment, education, age, and others, along with terrain and vehicle age. At-fault driver crash counts, normalized over …

Psychometric Properties Of A Working Memory Span Task, Juan M. Alzate Vanegas

Honors Undergraduate Theses

The intent of this thesis is to examine the psychometric properties of a complex span task (CST) developed to measure working memory capacity (WMC) using measurements obtained from a sample of 68 undergraduate students at the University of Central Florida. The Grocery List Task (GLT) promises several design improvements over traditional CSTs in a prior study about individual differences in WMC and distraction effects on driving performance, and it offers potential benefits for studying WMC as well as the serial-position effect. Currently, the working memory system is composed of domain-general memorial storage processes and information-processing, which involves the use of …

A Quantitative Analysis Of Intermediate Forms Within Astarte From The Atlantic Coastal Plain, Philip Roberson

Murray State Theses and Dissertations

The Atlantic Coastal Plain has long been recognized as a natural laboratory useful for testing hypotheses about various environmental and ecological effects on marine fauna. For studies such as these to continue being conducted in a rigorous and easily repeatable manner, a reliable taxonomy must be established for genera within this physiographic province. The bivalve genus, Astarte, is a cosmopolitan genus that is commonly found within the Atlantic Coastal Plain. This genus has many formally recognized species, even though it lacks many features that would encourage diversification, marking it as a taxonomic group in need of potential revision. The …

Prediction Intervals For Functional Data, Nicholas Rios

Theses, Dissertations and Culminating Projects

The prediction of functional data samples has been the focus of several functional data analysis endeavors. This work describes the use of dynamic function-on-function regression for dynamic prediction of the future trajectory as well as the construction of dynamic prediction intervals for functional data. The overall goals of this thesis are to assess the efficacy of Dynamic Penalized Function-on-Function Regression (DPFFR) and to compare DPFFR prediction intervals with those of other dynamic prediction methods. To make these comparisons, metrics are used that measure prediction error, prediction interval width, and prediction interval coverage. Simulations and applications to financial stock data from …

High Dimensional Multivariate Inference Under General Conditions, Xiaoli Kong

Theses and Dissertations--Statistics

In this dissertation, we investigate four distinct and interrelated problems for high-dimensional inference of mean vectors in multi-groups.

The first problem concerned is the profile analysis of high dimensional repeated measures. We introduce new test statistics and derive its asymptotic distribution under normality for equal as well as unequal covariance cases. Our derivations of the asymptotic distributions mimic that of Central Limit Theorem with some important peculiarities addressed with sufficient rigor. We also derive consistent and unbiased estimators of the asymptotic variances for equal and unequal covariance cases respectively.

The second problem considered is the accurate inference for high-dimensional repeated …

Using The Qbest Equation To Evaluate Ellagic Acid Safety Data: Generating A Qnoael With Confidence Levels From Disparate Literature, Cynthia Rose Dickerson

Theses and Dissertations--Pharmacy

QBEST, a novel statistical method, can be applied to the problem of estimating the No Observed Adverse Effect Level (NOAEL or QNOAEL) of a New Molecular Entity (NME) in order to anticipate a safe starting dose for beginning clinical trials. The NOAEL from QBEST (called the QNOAEL) can be calculated using multiple disparate studies in the literature and/or from the lab. The QNOAEL is similar in some ways to the Benchmark Dose Method (BMD) used widely in toxicological research, but is superior to the BMD in some ways. The QNOAEL simulation generates an intuitive curve that is comparable to the …

Understanding The Novice Decision-Making Process In Forensic Footwear Examinations: Accuracy And Decision Rules, Madonna A. Nobel

Graduate Theses, Dissertations, and Problem Reports (ETD)

The reproducibility of experienced-based forensic pattern interpretation is founded on the notion that domain-specific knowledge can be successfully distributed and applied among experts within a group. This assumption persists, even when the examination is complicated by variations in case circumstances, such as impression clarity and totality, as well as media, substrate, collection mechanism and enhancement. While it is further theorized that many of these factors (as well as additional confounding factors) are at play during an examination, the manner and extent to which these sources of variability affect the examination of footwear evidence remain unclear. In order to explore this …

Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez

Conference papers

Abstract—Metal oxide (MOX) gas detectors based on SnO2 provide low-cost solutions for real-time sensing of complex gas mixtures for indoor ambient monitoring. With high sensitivity under ideal conditions, MOX detectors may have poor longterm response accuracy due to environmental factors (humidity and temperature) along with sensor aging, leading to calibration drifts. Finding a simple and efficient solution to correct such calibration drifts has been the subject of numerous studies but remains an open problem. In this work, we present an efficient approach to MOX calibration using active and transfer sampling techniques coupled with non-linear machine learning algorithms, namely neural networks, …

Algorithms For Reconstruction Of Gene Regulatory Networks From High -Throughput Gene Expression Data, Wenping Deng

Dissertations, Master's Theses and Master's Reports

Understanding gene interactions in complex living systems is one of the central tasks in system biology. With the availability of microarray and RNA-Seq technologies, a multitude of gene expression datasets has been generated towards novel biological knowledge discovery through statistical analysis and reconstruction of gene regulatory networks (GRN). Reconstruction of GRNs can reveal the interrelationships among genes and identify the hierarchies of genes and hubs in networks. The new algorithms I developed in this dissertation are specifically focused on the reconstruction of GRNs with increased accuracy from microarray and RNA-Seq high-throughput gene expression data sets.

The first algorithm (Chapter 2) …

Offline And Online Density Estimation For Large High-Dimensional Data, Aref Majdara

Dissertations, Master's Theses and Master's Reports

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient.

This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is …