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Examination And Comparison Of The Performance Of Common Non-Parametric And Robust Regression Models, Gregory F. Malek 2017 Stephen F Austin State University

Examination And Comparison Of The Performance Of Common Non-Parametric And Robust Regression Models, Gregory F. Malek

Electronic Theses and Dissertations

ABSTRACT

Examination and Comparison of the Performance of Common Non-Parametric and Robust Regression Models

By

Gregory Frank Malek

Stephen F. Austin State University, Masters in Statistics Program,

Nacogdoches, Texas, U.S.A.

g_m_2002@live.com

This work investigated common alternatives to the least-squares regression method in the presence of non-normally distributed errors. An initial literature review identified a variety of alternative methods, including Theil Regression, Wilcoxon Regression, Iteratively Re-Weighted Least Squares, Bounded-Influence Regression, and Bootstrapping methods. These methods were evaluated using a simple simulated example data set, as well as various real data sets, including math proficiency data, Belgian telephone ...


Prediction Of Stress Increase In Unbonded Tendons Using Sparse Principal Component Analysis, Eric Mckinney 2017 Utah State University

Prediction Of Stress Increase In Unbonded Tendons Using Sparse Principal Component Analysis, Eric Mckinney

All Graduate Plan B and other Reports

While internal and external unbonded tendons are widely utilized in concrete structures, the analytic solution for the increase in unbonded tendon stress, Δ𝑓𝑝𝑠, is challenging due to the lack of bond between strand and concrete. Moreover, most analysis methods do not provide high correlation due to the limited available test data. In this thesis, Principal Component Analysis (PCA), and Sparse Principal Component Analysis (SPCA) are employed on different sets of candidate variables, amongst the material and sectional properties from the database compiled by Maguire et al. [18]. Predictions of Δ𝑓𝑝𝑠 are made via Principal Component Regression models, and the method ...


Uses Of The Hypergeometric Distribution For Determining Survival Or Complete Representation Of Subpopulations In Sequential Sampling, Brooke Busbee 2017 Stephen F Austin State University

Uses Of The Hypergeometric Distribution For Determining Survival Or Complete Representation Of Subpopulations In Sequential Sampling, Brooke Busbee

Electronic Theses and Dissertations

This thesis will explore the hypergeometric probability distribution by looking at many different aspects of the distribution. These include, and are not limited to: history and origin, derivation and elementary applications, properties, relationships to other probability models, kindred hypergeometric distributions and elements of statistical inference associated with the hypergeometric distribution. Once the above are established, an investigation into and furthering of work done by Walton (1986) and Charlambides (2005) will be done. Here, we apply the hypergeometric distribution to sequential sampling in order to determine a surviving subcategory as well as study the problem of and complete representation of the ...


Gender, Age, Research Experience, Leading Role And Academic Productivity Of Vietnamese Researchers In The Social Sciences And Humanities: Exploring A 2008-2017 Scopus Dataset, Quan-Hoang Vuong, Tung M. Ho, Thu-Trang Vuong, Nancy K. Napier, Hiep-Hung Pham, Ha V. Nguyen 2017 Universite Libre de Bruxelles

Gender, Age, Research Experience, Leading Role And Academic Productivity Of Vietnamese Researchers In The Social Sciences And Humanities: Exploring A 2008-2017 Scopus Dataset, Quan-Hoang Vuong, Tung M. Ho, Thu-Trang Vuong, Nancy K. Napier, Hiep-Hung Pham, Ha V. Nguyen

Quan-Hoang Vuong

Background: Academic productivity has been studied by scholars all round the world for many years. However, in Vietnam, this topic has scarcely been addressed. This research therefore aims at better understanding the correlations between gender, age, research experience, the leading role of corresponding authors, and the total number of their publications in the specific realm of social sciences and humanities.
Methods: The study employed a Scopus dataset with publication profiles of 410 Vietnamese researchers between 2008 and 2017.
Results: Men did not differ from women in academic publications (P=0.827). The proficiency of corresponding authors positively correlated with the ...


Methods For Scalar-On-Function Regression, Philip T. Reiss, Jeff Goldsmith, Han Lin Shang, R. Todd Ogden 2017 Columbia University

Methods For Scalar-On-Function Regression, Philip T. Reiss, Jeff Goldsmith, Han Lin Shang, R. Todd Ogden

Philip T. Reiss

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images, etc. are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorizing the basic model types as linear, nonlinear and nonparametric. We discuss publicly available software packages, and illustrate some of the procedures by application to a functional magnetic resonance imaging dataset.


Application Of Support Vector Machine Modeling And Graph Theory Metrics For Disease Classification, Jessica M. Rudd 2017 Kennesaw State University

Application Of Support Vector Machine Modeling And Graph Theory Metrics For Disease Classification, Jessica M. Rudd

Grey Literature from PhD Candidates

Disease classification is a crucial element of biomedical research. Recent studies have demonstrated that machine learning techniques, such as Support Vector Machine (SVM) modeling, produce similar or improved predictive capabilities in comparison to the traditional method of Logistic Regression. In addition, it has been found that social network metrics can provide useful predictive information for disease modeling. In this study, we combine simulated social network metrics with SVM to predict diabetes in a sample of data from the Behavioral Risk Factor Surveillance System. In this dataset, Logistic Regression outperformed SVM with ROC index of 81.8 and 81.7 for ...


An Investigation Of The Accuracy Of Parallel Analysis For Determining The Number Of Factors In A Factor Analysis, Mandy Matsumoto 2017 Western Kentucky University

An Investigation Of The Accuracy Of Parallel Analysis For Determining The Number Of Factors In A Factor Analysis, Mandy Matsumoto

Honors College Capstone Experience/Thesis Projects

Exploratory factor analysis is an analytic technique used to determine the number of factors in a set of data (usually items on a questionnaire) for which the factor structure has not been previously analyzed. Parallel analysis (PA) is a technique used to determine the number of factors in a factor analysis. There are a number of factors that affect the results of a PA: the choice of the eigenvalue percentile, the strength of the factor loadings, the number of variables, and the sample size of the study. Although PA is the most accurate method to date to determine which factors ...


Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson 2017 Illinois State University

Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson

Capstone Projects – Politics and Government

Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated ...


Discrimination By Gender And Disability Status: Do Worker Perceptions Match Statistical Measures?, Kevin F. Hallock, Wallace Hendricks, Emer Broadbent 2017 Cornell University

Discrimination By Gender And Disability Status: Do Worker Perceptions Match Statistical Measures?, Kevin F. Hallock, Wallace Hendricks, Emer Broadbent

Kevin F Hallock

We explore whether perceptions of discrimination are related to ordinary statistical measures. The majority of disabled respondents report feeling some discrimination due to their disability, the majority of women feel some discrimination because of their gender, and a surprising number of men also report some discrimination. We do not find a strong link between perceptions of discrimination and measured discrimination perhaps because those who perceive discrimination feel that it occurs along other dimensions than pay. However, we do find a connection between whether a person feels his or her income is inadequate and measured discrimination for all groups studied.


Estimating Pay Gaps For Workers With Disabilities: Implications From Broadening Definitions And Data Sets, Kevin F. Hallock, Xin Jin, Linda Barrington 2017 Cornell University

Estimating Pay Gaps For Workers With Disabilities: Implications From Broadening Definitions And Data Sets, Kevin F. Hallock, Xin Jin, Linda Barrington

Kevin F Hallock

Purpose: To compare pay gap estimates across 3 different national survey data sets for people with disabilities relative to those without disabilities when pay is measured as wage and salary alone versus a (total compensation) definition that includes an estimate of the value of benefits. Method: Estimates of the cost to the employers of employee benefits at the occupational level from an employer survey data set are matched to individual-level data in each of the 3 data sets. Multiple regression techniques are applied to estimate wage and salary and total compensation gaps between full-time men with and without disabilities. Results ...


Prediction Of Remaining Life Of Power Transformers Based On Left Truncated And Right Censored Lifetime Data, Yili Hong, William Q. Meeker, James D. McCalley 2017 Iowa State University

Prediction Of Remaining Life Of Power Transformers Based On Left Truncated And Right Censored Lifetime Data, Yili Hong, William Q. Meeker, James D. Mccalley

James McCalley

Prediction of the remaining life of high-voltage power transformers is an important issue for energy companies because of the need for planning maintenance and capital expenditures. Lifetime data for such transformers are complicated because transformer lifetimes can extend over many decades and transformer designs and manufacturing practices have evolved. We were asked to develop statistically-based predictions for the lifetimes of an energy company’s fleet of high-voltage transmission and distribution transformers. The company’s data records begin in 1980, providing information on installation and failure dates of transformers. Although the dataset contains many units that were installed before 1980, there ...


The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover 2017 University of Iowa

The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover

Diane Rover

This paper presents the evaluation of a program designed to improve transfer outcomes for community college students pursuing an engineering degree. The program, the Engineering Admissions Partnership Program (E-APP), was designed to improve the navigational success of community college transfer students through connections to the university. These connections include coordinated academic advising, peer-mentoring, campus visits, and online social and professional networks. The objective of the study is to determine the efficacy of the E-APP and its interventions, which will be measured by increased participation rates and increased university retention rates for E-APP participants. Outcome data for the students are analyzed ...


Tests Of Significance In Reversal Or Switchback Trials, A. E. Brandt 2017 Iowa State College

Tests Of Significance In Reversal Or Switchback Trials, A. E. Brandt

Research Bulletin (Iowa Agriculture and Home Economics Experiment Station)

By extending "Student's" t-test to differences higher than the first, a method is provided for analyzing the results of reyersal tests employing as many periods as are practical with the organism and test used. It is shown in Part II that identical results can be obtained by the methods of analysis of variance so that the investigator may at will use either the methods presented in Part I or those in Part II if but one attribute of the experimental units is measured. But, if the investigator has one or more other measures relevant to his experimental results and ...


Analyzing Baseball Data With R, Claudia Sison 2017 California Polytechnic State University, San Luis Obispo

Analyzing Baseball Data With R, Claudia Sison

Statistics

No abstract provided.


Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan McKinney 2017 California Polytechnic State University, San Luis Obispo

Gridiron-Gurus Final Report: Fantasy Football Performance Prediction, Kyle Tanemura, Michael Li, Erica Dorn, Ryan Mckinney

Computer Science

Gridiron Gurus is a desktop application that allows for the creation of custom AI profiles to help advise and compete against in a Fantasy Football setting. Our AI are capable of performing statistical prediction of players on both a season long and week to week basis giving them the ability to both draft and manage a fantasy football team throughout a season.


Uncovering Functional Relationships In Leukemia, Reginald McGee 2017 Mathematical Biosciences Institute

Uncovering Functional Relationships In Leukemia, Reginald Mcgee

Biology and Medicine Through Mathematics Conference

No abstract provided.


Methods For Parameter Estimation Of A Stochastic Seir Model, Kaitlyn Martinez 2017 Colorado School of Mines

Methods For Parameter Estimation Of A Stochastic Seir Model, Kaitlyn Martinez

Biology and Medicine Through Mathematics Conference

No abstract provided.


Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders, Amy Cochran 2017 University of Michigan-Ann Arbor

Using Mathematical Models Of Biological Processes In Genome-Wide Association Studies Of Psychiatric Disorders, Amy Cochran

Biology and Medicine Through Mathematics Conference

No abstract provided.


A Generalized Linear Model For Marital Disruption In Namibia, Lillian Pazvakawambwa 2017 University of Namibia, Department of Statistics and Population Studies

A Generalized Linear Model For Marital Disruption In Namibia, Lillian Pazvakawambwa

Andrews Research Conference

Marital disruption has attracted wide attention among researchers. In recent years, the world has experienced reductions in marriage rates, along with significant increases in cohabiting unions, divorce and separation, leading to rising conjugal and family instability. While some have seen this as a sign of social and moral disruption with a potential to shatter the family institution and the foundations of society itself, others have embraced these trends as signaling increased individual liberty and the loosening of suffocating social mores. There is limited research on the factors influencing marital disruption in Namibia. This paper used the Namibia Demographic and Health ...


Do You Know What Your Phone Is Doing To You? - Analysis On Usage Data Over An Entire Semester, Jawa El-Shanti 2017 Chapman University

Do You Know What Your Phone Is Doing To You? - Analysis On Usage Data Over An Entire Semester, Jawa El-Shanti

Student Research Day Abstracts and Posters

Like many teens today, I am a victim of cell phone addiction. Over the course of the spring 2017 semester I recorded my phone usage with the aim to quantify the degree of my addiction. I am using an iPhone application called Moment, which records the amount of time I spend on each application, the number of times I pick up my phone, and when I first and last used my phone during the day. I decided to keep track of the applications I want to minimize my time on which include Snapchat, Instagram, Netflix, YouTube and Messages. I am ...


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