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Articles 211 - 240 of 522

Full-Text Articles in Multivariate Analysis

The Principal Problem With Principal Components Regression, Gary N. Smith, Heidi Margaret Artigue Jan 2019

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

Pomona Economics

No abstract provided.


Step Away From Stepwise, Gary N. Smith Jan 2019

Step Away From Stepwise, Gary N. Smith

Pomona Economics

Stepwise regression is a popular data-mining tool that uses statistical significance to select the explanatory variables to be used in a multiple-regression model. A fundamental problem with stepwise regression is that some real explanatory variables that have causal effects on the dependent variable may happen to not be statistically significant, while nuisance variables may be coincidentally significant. As a result, the model may fit the data well in-sample, but do poorly out-of-sample. Many Big-Data researchers believe that, the larger the number of possible explanatory variables, the more useful is stepwise regression for selecting explanatory variables. The reality is that stepwise …


The Dark Sky Character Of Archaeological Landscapes: Cultural Meaning And Conservation Strategies, Frank Prendergast Jan 2019

The Dark Sky Character Of Archaeological Landscapes: Cultural Meaning And Conservation Strategies, Frank Prendergast

Book/Book Chapter

This paper presents the first ever study of light pollution at selected Irish prehistoric archaeological landscapes. The concepts of cosmology and landscape are first briefly described and followed by a summary of early human settlement of the island. Building on this, the extant corpus of early prehistoric megalithic burial tombs is illustrated to show their contrasting distribution patterns and typology. Analysis of tomb locations using nearest-neighbour statistical methods reveals evidence of intentional clustering. Further geo-statistical analysis identifies the geographical locations and the density ranking of these nucleated clusters - a feature especially evident in the passage tomb tradition on this …


Essays On Mixture Models, Trevor R. Camper Jan 2019

Essays On Mixture Models, Trevor R. Camper

College of Graduate Studies: Theses & Dissertations

When considering statistical scenarios where one can sample from populations that are not of interest for the purposes of a study, bivariate mixture models can be used to study the effect that this missampling can have on parameter estimation. In this thesis, we will examine the behavior that bivariate mixture models have on two statistical constructs: Cronbach's alpha \cite{C51}, and Spearman's rho \cite{S04}. Chapter 1 will introduce notions of mixture models and the definition of bias under mixture models which will serve as the central concept of this thesis. Chapter 2 will investigate a particular psychometric issue known as insufficient …


Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya Jan 2019

Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya

College of Graduate Studies: Theses & Dissertations

Variable selection is one of the standard ways of selecting models in large scale datasets. It has applications in many fields of research study, especially in large multi-center clinical trials. One of the prominent methods in variable selection is the penalized likelihood, which is both consistent and efficient. However, the penalized selection is significantly challenging under the influence of random (frailty) covariates. It is even more complicated when there is involvement of censoring as it may not have a closed-form solution for the marginal log-likelihood. Therefore, we applied the penalized quasi-likelihood (PQL) approach that approximates the solution for such a …


Biodiversity And Distribution Of Benthic Foraminifera In Harrington Sound, Bermuda: The Effects Of Physical And Geochemical Factors On Dominant Taxa, Nam Le Jan 2019

Biodiversity And Distribution Of Benthic Foraminifera In Harrington Sound, Bermuda: The Effects Of Physical And Geochemical Factors On Dominant Taxa, Nam Le

Honors Theses

Harrington Sound, Bermuda, is a nearly enclosed lagoon acting as a subtropical/tropical, carbonate-rich basin in which carbonate sediments, reef patches, and carbonate-producing organisms accumulate. Here, one of the most important calcareous groups is the Foraminifera. Analyses of common benthic orders, including miliolids (Quinqueloculina and Triloculina spp.) and rotaliids (Homotrema rubrum, Elphidium spp., and Ammonia beccarii), are essential in understanding past and present environmental conditions affecting the island's coastal environment. These taxa have been studied previously; however, factors explaining their individual patterns of abundance in the Sound are not well detailed. The goal of this study is …


Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson Jan 2019

Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson

All Master's Theses

Artiodactyl bones are the most common faunal remains found in Washington prehistoric archaeology sites, but they are often too fragmented to accurately identify a family, genus, or species. Traditional faunal analysis can only organize unidentifiable bone fragments into size class, and chemical methods often require the destruction of bone samples. In this thesis research, I tested a new, nondestructive faunal analysis technique using portable X-ray fluorescence (pXRF) to measure trace element concentrations in comparative collection and archaeological bone samples. Using cannonbones from five different artiodactyl species, I collected trace element data from 50 comparative collection specimens and 18 archaeological specimens …


Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane Jan 2019

Modeling Stochastically Intransitive Relationships In Paired Comparison Data, Ryan Patrick Alexander Mcshane

Statistical Science Theses and Dissertations

If the Warriors beat the Rockets and the Rockets beat the Spurs, does that mean that the Warriors are better than the Spurs? Sophisticated fans would argue that the Warriors are better by the transitive property, but could Spurs fans make a legitimate argument that their team is better despite this chain of evidence?

We first explore the nature of intransitive (rock-scissors-paper) relationships with a graph theoretic approach to the method of paired comparisons framework popularized by Kendall and Smith (1940). Then, we focus on the setting where all pairs of items, teams, players, or objects have been compared to …


A New Independence Measure And Its Applications In High Dimensional Data Analysis, Chenlu Ke Jan 2019

A New Independence Measure And Its Applications In High Dimensional Data Analysis, Chenlu Ke

Theses and Dissertations--Statistics

This dissertation has three consecutive topics. First, we propose a novel class of independence measures for testing independence between two random vectors based on the discrepancy between the conditional and the marginal characteristic functions. If one of the variables is categorical, our asymmetric index extends the typical ANOVA to a kernel ANOVA that can test a more general hypothesis of equal distributions among groups. The index is also applicable when both variables are continuous. Second, we develop a sufficient variable selection procedure based on the new measure in a large p small n setting. Our approach incorporates marginal information between …


Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data, Jiaying Weng Jan 2019

Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data, Jiaying Weng

Theses and Dissertations--Statistics

The big data era poses great challenges as well as opportunities for researchers to develop efficient statistical approaches to analyze massive data. Sufficient dimension reduction is such an important tool in modern data analysis and has received extensive attention in both academia and industry.

In this dissertation, we introduce inverse regression estimators using Fourier transforms, which is superior to the existing SDR methods in two folds, (1) it avoids the slicing of the response variable, (2) it can be readily extended to solve the high dimensional data problem. For the ultra-high dimensional problem, we investigate both eigenvalue decomposition and minimum …


Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis Jan 2019

Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis

College of Graduate Studies: Theses & Dissertations

Self-care activities classification poses significant challenges in identifying children’s unique functional abilities and needs within the exceptional children healthcare system. The accuracy of diagnosing a child's self-care problem, such as toileting or dressing, is highly influenced by an occupational therapists’ experience and time constraints. Thus, there is a need for objective means to detect and predict in advance the self-care problems of children with physical and motor disabilities. We use clustering to discover interesting information from self-care problems, perform automatic classification of binary data, and discover outliers. The advantages are twofold: the advancement of knowledge on identifying self-care problems in …


Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos Jan 2019

Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos

Theses and Dissertations--Statistics

This dissertation focuses on the problem of making high-dimensional inference for two or more groups. High-dimensional means both the sample size (n) and dimension (p) tend to infinity, possibly at different rates. Classical approaches for group comparisons fail in the high-dimensional situation, in the sense that they have incorrect sizes and low powers. Much has been done in recent years to overcome these problems. However, these recent works make restrictive assumptions in terms of the number of treatments to be compared and/or the distribution of the data. This research aims to (1) propose and investigate refined …


The Effect Of Vegetative Structure On Nest-Burrow Selection By The Western Burrowing Owl: Comparing Traditional Methods To Photogrammetry With An Unmanned Aerial System, Dylan J. Steffen Jan 2019

The Effect Of Vegetative Structure On Nest-Burrow Selection By The Western Burrowing Owl: Comparing Traditional Methods To Photogrammetry With An Unmanned Aerial System, Dylan J. Steffen

Master's Theses or Doctor of Nursing Practice

The shortgrass prairie ecoregion in the United States has been reduced to 52% of its historical extent, contributing to reduced habitat for native species. One such species is the Burrowing Owl (Athene cunicularia). The Western Burrowing Owl subspecies (A. c. hypugaea) is listed as a Species of Special Concern in nearly every western and midwestern state, including Kansas where it is designated as a Tier II Species of Greatest Conservation Need. Habitat destruction due to conversion to cropland, increasing use of pesticides, and reduction in burrowing mammal abundance are the primary threats that have led to …


Compound-Specific Isotope Analysis Of Amino Acids In Biological Tissues: Applications In Forensic Entomology, Food Authentication And Soft-Biometrics In Humans, Mayara Patricia Viana De Matos Jan 2019

Compound-Specific Isotope Analysis Of Amino Acids In Biological Tissues: Applications In Forensic Entomology, Food Authentication And Soft-Biometrics In Humans, Mayara Patricia Viana De Matos

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this work we demonstrate the power of compound-specific isotope analysis (CSIA) to analyze proteinaceous biological materials in three distinct forensic applications, including: 1) linking necrophagous blow flies in different life stages to their primary carrion diet; 2) identifying the harvesting area of oysters for food authentication purposes; and 3) the ability to predict biometric traits about humans from their hair.

In the first application, we measured the amino-acid-level fractionation that occurs at each major life stage of Calliphora vicina (Robineau-Desvoidy) (Diptera: Calliphoridae) blow flies. Adult blow flies oviposited on raw pork muscle, beef muscle, or chicken liver. Larvae, pupae …


The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith Dec 2018

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 Dec 2018

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 Oct 2018

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 Oct 2018

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 Aug 2018

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 Aug 2018

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 Jul 2018

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 3rd 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-CourtTM (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 Jun 2018

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 Jun 2018

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 May 2018

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 May 2018

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 May 2018

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 May 2018

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 May 2018

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 Apr 2018

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 Apr 2018

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 …