Nonparametric Tests Of Lack Of Fit For Multivariate Data,
2020
University of Kentucky
Nonparametric Tests Of Lack Of Fit For Multivariate Data, Yan Xu
Theses and Dissertations--Statistics
A common problem in regression analysis (linear or nonlinear) is assessing the lack-of-fit. Existing methods make parametric or semi-parametric assumptions to model the conditional mean or covariance matrices. In this dissertation, we propose fully nonparametric methods that make only additive error assumptions. Our nonparametric approach relies on ideas from nonparametric smoothing to reduce the test of association (lack-of-fit) problem into a nonparametric multivariate analysis of variance. A major problem that arises in this approach is that the key assumptions of independence and constant covariance matrix among the groups will be violated. As a result, the standard asymptotic theory is not …
Measuring Variability In Model Performance Measures,
2020
University of Kentucky
Measuring Variability In Model Performance Measures, Matthew Rutledge
Theses and Dissertations--Statistics
As data become increasingly available, statisticians are confronted with both larger sample sizes and larger numbers of predictors. While both of these factors are beneficial in building better predictive models and allowing for better inference, models can become difficult to interpret and often include variables of little practical significance. This dissertation provides methods that assist model builders to better understand and select from a collection of candidate models. We study the asymptotic distribution of AIC and propose a graphical tool to assist practitioners in comparing and contrasting candidate models. Real-world examples show how this graphic might be used and a …
Contemporary Epidemiology Of Rising Atrial Septal Defect Trends Across Usa 1991–2016: A Combined Ecological Geospatiotemporal And Causal Inferential Study,
2020
Edith Cowan University
Contemporary Epidemiology Of Rising Atrial Septal Defect Trends Across Usa 1991–2016: A Combined Ecological Geospatiotemporal And Causal Inferential Study, Albert Stuart Reece, Gary Kenneth Hulse
Research outputs 2014 to 2021
© 2020, The Author(s). Background: Cardiovascular anomalies are the largest group of congenital anomalies and the major cause of death in young children, with various data linking rising atrial septal defect incidence (ASDI) with prenatal cannabis exposure. Objectives / Hypotheses. Is cannabis associated with ASDI in USA? Is this relationship causal? Methods: Geospatiotemporal cohort study, 1991–2016. Census populations of adults, babies, congenital anomalies, income and ethnicity. Drug exposure data on cigarettes, alcohol abuse, past month cannabis use, analgesia abuse and cocaine taken from National Survey of Drug Use and Health (78.9% response rate). Cannabinoid concentrations from Drug Enforcement Agency. Inverse …
Modelling Interactions Among Offenders: A Latent Space Approach For Interdependent Ego-Networks,
2020
University College Dublin
Modelling Interactions Among Offenders: A Latent Space Approach For Interdependent Ego-Networks, Isabella Gollini, Alberto Caimo, Paolo Campana
Articles
Illegal markets are notoriously difficult to study. Police data offer an increasingly exploited source of evidence. However, their secondary nature poses challenges for researchers. A key issue is that researchers often have to deal with two sets of actors: targeted and non-targeted. This work develops a latent space model for interdependent ego-networks purposely created to deal with the targeted nature of police evidence. By treating targeted offenders as egos and their contacts as alters, the model (a) leverages on the full information available and (b) mirrors the specificity of the data collection strategy. The paper then applies this approach to …
The Economic Determinants Of American Professional Sports Franchise Valuations,
2020
Western Kentucky University
The Economic Determinants Of American Professional Sports Franchise Valuations, Ryan Flora
Mahurin Honors College Capstone Experience/Thesis Projects
This thesis seeks to analyze the impact of regional identities on American professional sports team valuations. Regional identities are classified as any name of a team that is not tied directly to the city that they reside in. For example, the Carolina Panthers have a regional identity because they are not based out of “Carolina”, they are based out of Charlotte, North Carolina. Another example would be the Arizona Cardinals, whose name encompasses the whole state of Arizona rather than Phoenix, the city they are based out of. The leagues that will be involved in this study are the National …
Psychometric Analysis Of Forensic Examiner Behavior,
2020
Swarthmore College
Psychometric Analysis Of Forensic Examiner Behavior, Amanda Luby, A. Mazumder, B. Junker
Mathematics & Statistics Faculty Works
Forensic science often involves the comparison of crime-scene evidence to a known-source sample to determine if the evidence and the reference sample came from the same source. Even as forensic analysis tools become increasingly objective and automated, final source identifications are often left to individual examiners’ interpretation of the evidence. Each source identification relies on judgements about the features and quality of the crime-scene evidence that may vary from one examiner to the next. The current approach to characterizing uncertainty in examiners’ decision-making has largely centered around the calculation of error rates aggregated across examiners and identification tasks, without taking …
Spatial And Temporal Genetic Structure Of Winter-Run Steelhead (Oncorhynchus Mykiss) Returning To The Mad River, California,
2020
Humboldt State University
Spatial And Temporal Genetic Structure Of Winter-Run Steelhead (Oncorhynchus Mykiss) Returning To The Mad River, California, Steven R. Fong
Cal Poly Humboldt theses and projects
Distinct populations of steelhead in the wild are in decline. The propagation of steelhead in hatcheries has been used to boost population numbers for recreational fisheries and for use in conservation. However, hatchery breeding practices of steelhead can result in changes in genetic structure. I investigated the genetic structure of winter-run steelhead (Oncorhynchus mykiss) returning to the Mad River, California, where a hatchery has been used enhance production for recreational fisheries since 1971. Genetic variability in Mad River steelhead was evaluated using 96 single nucleotide polymorphisms (SNPs) among 4203 individuals, including the Mad River and nearby locations, and …
Short-Term Effects Of Ambient Ozone, Pm2. 5, And Meteorological Factors On Covid-19 Confirmed Cases And Deaths In Queens, New York.,
2020
Georgia Southern University, Jiann-Ping Hsu College of Public Health
Short-Term Effects Of Ambient Ozone, Pm2. 5, And Meteorological Factors On Covid-19 Confirmed Cases And Deaths In Queens, New York., Atin Adhikari, Jingjing Yin
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, has been rapidly increasing in the United States. Boroughs of New York City, including Queens county, turn out to be the epicenters of this infection. According to the data provided by the New York State Department of Health, most of the cases of new COVID-19 infections in New York City have been found in the Queens county where 42,023 people have tested positive, and 3221 people have died as of 20 April 2020. Person-to-person transmission and travels were implicated in the initial spread of the outbreaks, but factors …
Molecular Typing Of Rickettsia Akari,
2020
Georgia Southern University, Jiann-Ping Hsu College of Public Health
Molecular Typing Of Rickettsia Akari, Marina E. Eremeeva
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
Rickettsia akari is an obligate intracellular bacterium that causes smallpox rickettsia. Rickettsia akari is an atypical member of the rickettsia spotted fever (SFG) group because it circulates in gamasid mites; however, only limited data are available regarding the degree of genetic diversity of R. akari isolates. We examined 13 isolates of R. akari isolated from humans, rodents, and ticks in the United States, the countries of the former USSR, and the former Yugoslavia for the period from 1946 to 2003 for diversity in the composition of tandem repeats (TR) and intergenic regions (IGR). Using the Tandem Repeat Finder software (http://tandem.bu.edu) …
Imputation Of Missing Data From Time-Lapse Cameras Used In Recreational Fishing Surveys,
2020
Edith Cowan University
Imputation Of Missing Data From Time-Lapse Cameras Used In Recreational Fishing Surveys, Ebenezer Afrifa-Yamoah, Stephen M. Taylor, Aiden Fisher, Ute Mueller
Research outputs 2014 to 2021
While remote camera surveys have the potential to improve the accuracy of recreational fishing estimates, missing data are common and require robust analytical techniques to impute. Time-lapse cameras are being used in Western Australia to monitor recreational boating activities, but outages have occurred. Generalized linear mixed effect models formulated in a fully conditional specification multiple imputation framework were used to reconstruct missing data, with climatic and some temporal classifications as covariates. Using a complete 12-month camera record of hourly counts of recreational powerboat retrievals, data were simulated based on ten observed camera outage patterns, with a missing proportion of between …
Multiple Imputation Using Influential Exponential Tilting In Case Of Non-Ignorable Missing Data,
2020
Jiann Ping HSU College of Public Health
Multiple Imputation Using Influential Exponential Tilting In Case Of Non-Ignorable Missing Data, Kavita Gohil
College of Graduate Studies: Theses & Dissertations
Modern research strategies rely predominantly on three steps, data collection, data analysis, and inference. In research, if the data is not collected as designed, researchers may face challenges of having incomplete data, especially when it is non-ignorable. These situations affect the subsequent steps of evaluation and make them difficult to perform. Inference with incomplete data is a challenging task in data analysis and clinical trials when missing data related to the condition under the study. Moreover, results obtained from incomplete data are prone to biases. Parameter estimation with non-ignorable missing data is even more challenging to handle and extract useful …
Public Perception Of Different Planting Techniques Using Augmented Reality,
2020
Georgia Southern University
Public Perception Of Different Planting Techniques Using Augmented Reality, Sultana Quader Tania
College of Graduate Studies: Theses & Dissertations
The objective of this study was to measure public perception of the different planting techniques (block and matrix), which are used at visitor information centers (VICs) and other rights of way (ROW) areas. The main factors that affect public perception of planting techniques were identified through an extensive literature review and qualitative survey from four welcome centers in the state of Georgia. The ranking of those indicators, based on public preferences, was discovered through a quantitative survey. During the first phase of the quantitative survey, images of block and matrix were used. An iOS-based user-friendly and cost-effective augmented reality (AR) …
Nonparametric Misclassification Simulation And Extrapolation Method And Its Application,
2020
Georgia Southern University
Nonparametric Misclassification Simulation And Extrapolation Method And Its Application, Congjian Liu
College of Graduate Studies: Theses & Dissertations
The misclassification simulation extrapolation (MC-SIMEX) method proposed by Küchenho et al. is a general method of handling categorical data with measurement error. It consists of two steps, the simulation and extrapolation steps. In the simulation step, it simulates observations with varying degrees of measurement error. Then parameter estimators for varying degrees of measurement error are obtained based on these observations. In the extrapolation step, it uses a parametric extrapolation function to obtain the parameter estimators for data with no measurement error. However, as shown in many studies, the parameter estimators are still biased as a result of the parametric extrapolation …
Generalization Of Kullback-Leibler Divergence For Multi-Stage Diseases: Application To Diagnostic Test Accuracy And Optimal Cut-Points Selection Criterion,
2020
Georgia Southern University
Generalization Of Kullback-Leibler Divergence For Multi-Stage Diseases: Application To Diagnostic Test Accuracy And Optimal Cut-Points Selection Criterion, Chen Mo
College of Graduate Studies: Theses & Dissertations
The Kullback-Leibler divergence (KL), which captures the disparity between two distributions, has been considered as a measure for determining the diagnostic performance of an ordinal diagnostic test. This study applies KL and further generalizes it to comprehensively measure the diagnostic accuracy test for multi-stage (K > 2) diseases, named generalized total Kullback-Leibler divergence (GTKL). Also, GTKL is proposed as an optimal cut-points selection criterion for discriminating subjects among different disease stages. Moreover, the study investigates a variety of applications of GTKL on measuring the rule-in/out potentials in the single-stage and multi-stage levels. Intensive simulation studies are conducted to compare the performance …
Artificial Neural Network Models For Pattern Discovery From Ecg Time Series,
2020
Georgia Southern University
Artificial Neural Network Models For Pattern Discovery From Ecg Time Series, Mehakpreet Kaur
College of Graduate Studies: Theses & Dissertations
Artificial Neural Network (ANN) models have recently become de facto models for deep learning with a wide range of applications spanning from scientific fields such as computer vision, physics, biology, medicine to social life (suggesting preferred movies, shopping lists, etc.). Due to advancements in computer technology and the increased practice of Artificial Intelligence (AI) in medicine and biological research, ANNs have been extensively applied not only to provide quick information about diseases, but also to make diagnostics accurate and cost-effective. We propose an ANN-based model to analyze a patient's electrocardiogram (ECG) data and produce accurate diagnostics regarding possible heart diseases …
Introduction To Game Theory: A Discovery Approach,
2020
Linfield College
Introduction To Game Theory: A Discovery Approach, Jennifer Firkins Nordstrom
Linfield Authors Book Gallery
Game theory is an excellent topic for a non-majors quantitative course as it develops mathematical models to understand human behavior in social, political, and economic settings. The variety of applications can appeal to a broad range of students. Additionally, students can learn mathematics through playing games, something many choose to do in their spare time! This text also includes an exploration of the ideas of game theory through the rich context of popular culture. It contains sections on applications of the concepts to popular culture. It suggests films, television shows, and novels with themes from game theory. The questions in …
Bayesian Kinetic Modeling For Tracer-Based Metabolomic Data,
2020
University of Kentucky
Bayesian Kinetic Modeling For Tracer-Based Metabolomic Data, Xu Zhang
Theses and Dissertations--Statistics
Kinetic modeling of the time dependence of metabolite concentrations including the unstable isotope labeled species is an important approach to simulate metabolic pathway dynamics. It is also essential for quantitative metabolic flux analysis using tracer data. However, as the metabolic networks are complex including extensive compartmentation and interconnections, the parameter estimation for enzymes that catalyze individual reactions needed for kinetic modeling is challenging. As the pa- rameter space is large and multi-dimensional while kinetic data are comparatively sparse, the estimation procedure (especially the point estimation methods) often en- counters multiple local maximum such that standard maximum likelihood methods may yield …
Statistical Intervals For Various Distributions Based On Different Inference Methods,
2020
University of Kentucky
Statistical Intervals For Various Distributions Based On Different Inference Methods, Yixuan Zou
Theses and Dissertations--Statistics
Statistical intervals (e.g., confidence, prediction, or tolerance) are widely used to quantify uncertainty, but complex settings can create challenges to obtain such intervals that possess the desired properties. My thesis will address diverse data settings and approaches that are shown empirically to have good performance. We first introduce a focused treatment on using a single-layer bootstrap calibration to improve the coverage probabilities of two-sided parametric tolerance intervals for non-normal distributions. We then turn to zero-inflated data, which are commonly found in, among other areas, pharmaceutical and quality control applications. However, the inference problem often becomes difficult in the presence of …
Moment Kernels For T-Central Subspace,
2020
University of Kentucky
Moment Kernels For T-Central Subspace, Weihang Ren
Theses and Dissertations--Statistics
The T-central subspace allows one to perform sufficient dimension reduction for any statistical functional of interest. We propose a general estimator using a third moment kernel to estimate the T-central subspace. In particular, in this dissertation we develop sufficient dimension reduction methods for the central mean subspace via the regression mean function and central subspace via Fourier transform, central quantile subspace via quantile estimator and central expectile subsapce via expectile estima- tor. Theoretical results are established and simulation studies show the advantages of our proposed methods.
Measuring Change: Prediction Of Early Onset Sepsis,
2020
University of Kentucky
Measuring Change: Prediction Of Early Onset Sepsis, Aric Schadler
Theses and Dissertations--Statistics
Sepsis occurs in a patient when an infection enters into the blood stream and spreads throughout the body causing a cascading response from the immune system. Sepsis is one of the leading causes of morbidity and mortality in today’s hospitals. This is despite published and accepted guidelines for timely and appropriate interventions for septic patients. The largest barrier to applying these interventions is the early identification of septic patients. Early identification and treatment leads to better outcomes, shorter lengths of stay, and financial savings for healthcare institutions. In order to increase the lead time in recognizing patients trending towards septicemia …
