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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 ...


Thermodynamics Of Coherent Structures Near Phase Transitions, Julia M. Meyer, Ivan Christov 2017 Purdue University

Thermodynamics Of Coherent Structures Near Phase Transitions, Julia M. Meyer, Ivan Christov

The Summer Undergraduate Research Fellowship (SURF) Symposium

Phase transitions within large-scale systems may be modeled by nonlinear stochastic partial differential equations in which system dynamics are captured by appropriate potentials. Coherent structures in these systems evolve randomly through time; thus, statistical behavior of these fields is of greater interest than particular system realizations. The ability to simulate and predict phase transition behavior has many applications, from material behaviors (e.g., crystallographic phase transformations and coherent movement of granular materials) to traffic congestion. Past research focused on deriving solutions to the system probability density function (PDF), which is the ground-state wave function squared. Until recently, the extent to ...


A Characterization Of A Value Added Model And A New Multi-Stage Model For Estimating Teacher Effects Within Small School Systems, Julie M. Garai 2017 University of Nebraska-Lincoln

A Characterization Of A Value Added Model And A New Multi-Stage Model For Estimating Teacher Effects Within Small School Systems, Julie M. Garai

Dissertations and Theses in Statistics

At both the national and state level there is increasing pressure to develop metrics to determine if school systems are meeting educational objectives. All states mandate some form of assessment by standardized tests. One method currently used to model student test scores is Value Added Modeling (VAM), which models student scores as a product of classroom and school environments. One VAM approach is the Tennessee Value Added Assessment System (TVAAS) which models student gains from year to year. Teacher effects are included in this layered model, which estimates the teacher’s added value to a student score through best linear ...


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 ...


Classification With Large Sparse Datasets: Convergence Analysis And Scalable Algorithms, Xiang Li 2017 The University of Western Ontario

Classification With Large Sparse Datasets: Convergence Analysis And Scalable Algorithms, Xiang Li

Electronic Thesis and Dissertation Repository

Large and sparse datasets, such as user ratings over a large collection of items, are common in the big data era. Many applications need to classify the users or items based on the high-dimensional and sparse data vectors, e.g., to predict the profitability of a product or the age group of a user, etc. Linear classifiers are popular choices for classifying such datasets because of their efficiency. In order to classify the large sparse data more effectively, the following important questions need to be answered.

1. Sparse data and convergence behavior. How different properties of a dataset, such as ...


Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei 2017 STATinMED Research/SIMR, Inc.

Burden Of Atopic Dermatitis In The United States: Analysis Of Healthcare Claims Data In The Commercial, Medicare, And Medi-Cal Databases, Sulena Shrestha, Raymond Miao, Li Wang, Jingdong Chao, Huseyin Yuce, Wenhui Wei

Publications and Research

Comparative data on the burden of atopic dermatitis (AD) in adults relative to the general population are limited. We performed a large-scale evaluation of the burden of disease among US adults with AD relative to matched non-AD controls, encompassing comorbidities, healthcare resource utilization (HCRU), and costs, using healthcare claims data. The impact of AD disease severity on these outcomes was also evaluated.


Factor Based Statistical Arbitrage In The U.S. Equity Market With A Model Breakdown Detection Process, Seoungbyung park 2017 Marquette University

Factor Based Statistical Arbitrage In The U.S. Equity Market With A Model Breakdown Detection Process, Seoungbyung Park

Master's Theses (2009 -)

Many researchers have studied different strategies of statistical arbitrage to provide a steady stream of returns that are unrelated to the market condition. Among different strategies, factor-based mean reverting strategies have been popular and covered by many. This thesis aims to add value by evaluating the generalized pairs trading strategy and suggest enhancements to improve out-of-sample performance. The enhanced strategy generated the daily Sharpe ratio of 6.07% in the out-of-sample period from January 2013 through October 2016 with the correlation of -.03 versus S&P 500. During the same period, S&P 500 generated the Sharpe ratio of 6 ...


Mixture Models For Undiagnosed Prevalent Disease And Interval-Censored Incident Disease: Applications To A Cohort Assembled From Electronic Health Records., Li C Cheung, Qing Pan, Noorie Hyun, Mark Schiffman, Barbara Fetterman, Philip E Castle, Thomas Lorey, Hormuzd A Katki 2017 George Washington University

Mixture Models For Undiagnosed Prevalent Disease And Interval-Censored Incident Disease: Applications To A Cohort Assembled From Electronic Health Records., Li C Cheung, Qing Pan, Noorie Hyun, Mark Schiffman, Barbara Fetterman, Philip E Castle, Thomas Lorey, Hormuzd A Katki

Epidemiology and Biostatistics Faculty Publications

For cost-effectiveness and efficiency, many large-scale general-purpose cohort studies are being assembled within large health-care providers who use electronic health records. Two key features of such data are that incident disease is interval-censored between irregular visits and there can be pre-existing (prevalent) disease. Because prevalent disease is not always immediately diagnosed, some disease diagnosed at later visits are actually undiagnosed prevalent disease. We consider prevalent disease as a point mass at time zero for clinical applications where there is no interest in time of prevalent disease onset. We demonstrate that the naive Kaplan-Meier cumulative risk estimator underestimates risks at early ...


Strategies To Stabilize Locally Grown Produce For Year-Round Sales: A Feasibility Study, Sam Beattie, Lester Wilson, Aubrey Mendonca, Stéphanie Jung 2017 Iowa State University

Strategies To Stabilize Locally Grown Produce For Year-Round Sales: A Feasibility Study, Sam Beattie, Lester Wilson, Aubrey Mendonca, Stéphanie Jung

Stéphanie Jung

Local markets are dependent on fresh-grown products that are available only on a seasonal basis. This project looked at possible ways to preserve fruits and vegetables for profitable sales in the offseason.


Gelatinization Properties Of Starches From Three Successive Generations Of Six Exotic Corn Lines Grown In Two Locations, Y. Ji, L. M. Pollak, S. Duvick, K. Seetharaman, Philip Dixon, Pamela J. White 2017 Iowa State University

Gelatinization Properties Of Starches From Three Successive Generations Of Six Exotic Corn Lines Grown In Two Locations, Y. Ji, L. M. Pollak, S. Duvick, K. Seetharaman, Philip Dixon, Pamela J. White

Philip Dixon

The objectives of this research were to evaluate the intra- and interpopulation variability in gelatinization properties of starches from exotic corn lines and their derivatives when grown 1) during two successive years in the same location; and 2) in both temperate and tropical environments. Six novel exotic corn lines (two 100% exotic and four 25% exotic derived from a breeding cross developed by crossing an exotic hybrid with Corn Belt lines) were selected for this research because their starches have significantly different (and potentially useful) thermal properties from those found in starch from normal Corn Belt corn. The Sn (n ...


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.


Mechanistic Mathematical Models: An Underused Platform For Hpv Research, Marc Ryser, Patti Gravitt, Evan R. Myers 2017 George Washington University

Mechanistic Mathematical Models: An Underused Platform For Hpv Research, Marc Ryser, Patti Gravitt, Evan R. Myers

Global Health Faculty Publications

Health economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the ...


Methods For Estimating Usual Intake Distributions, Alicia L. Carriquiry, Helen H. Jensen, Wayne A. Fuller, P. Guenther 2017 Iowa State University

Methods For Estimating Usual Intake Distributions, Alicia L. Carriquiry, Helen H. Jensen, Wayne A. Fuller, P. Guenther

Alicia L. Carriquiry

Assessments of dietary adequacy should rely on estimating usual nutrient intake distributions. Such estimates for a population may be obtained from data collected in dietary surveys. We propose a semiparametric approach to transform the observed intake data, which are not normally distributed, into normality and to remove the dependence between individual intake means and variances.


Firing Rate Heterogeneity And Consequences For Coding In Feedforward Circuits, Cheng Ly, Gary Marsat 2017 Virginia Commonwealth University

Firing Rate Heterogeneity And Consequences For Coding In Feedforward Circuits, Cheng Ly, Gary Marsat

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.


Shape Features Underlying The Perception Of Liquids, Jan Jaap R. van Assen, Pascal Barla, Roland W. Fleming 2017 Department of Psychology, Justus-Liebig-University Giessen

Shape Features Underlying The Perception Of Liquids, Jan Jaap R. Van Assen, Pascal Barla, Roland W. Fleming

MODVIS Workshop

No abstract provided.


Mortgage Transition Model Based On Loanperformance Data, Shuyao Yang 2017 Washington University in St. Louis

Mortgage Transition Model Based On Loanperformance Data, Shuyao Yang

Arts & Sciences Electronic Theses and Dissertations

The unexpected increase in loan default on the mortgage market is widely considered to be one of the main cause behind the economic crisis. To provide some insight on loan delinquency and default, I analyze the mortgage performance data from Fannie Mae website and investigate how economic factors and individual loan and borrower information affect the events of default and prepaid. Various delinquency status including default and prepaid are treated as discrete states of a Markov chain. One-step transition probabilities are estimated via multinomial logistic models. We find that in general current loan-to-value ratio, credit score, unemployment rate, and interest ...


Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons 2017 Chapman University

Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons

Student Research Day Abstracts and Posters

After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.

I created a dataset of qualitative and quantitative outcomes from my ...


Comparision Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers, Richard Cutler Dr. 2017 Utah State University

Comparision Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers, Richard Cutler Dr.

All Graduate Plan B and other Reports

Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available ...


A Comparison Of Statistical Methods Relating Pairwise Distance To A Binary Subject-Level Covariate, Rachael Stone 2017 Utah State University

A Comparison Of Statistical Methods Relating Pairwise Distance To A Binary Subject-Level Covariate, Rachael Stone

All Graduate Plan B and other Reports

A community ecologist provided a motivating data set involving a certain animal species with two behavior groups, along with a pairwise genetic distance matrix among individuals. Many community ecologists have analyzed similar data sets with a method known as the Hopkins method, testing for an association between the subject-level covariate (behavior group) and the pairwise distance. This community ecologist wanted to know if they used the Hopkins method, would their results be meaningful? Their question inspired this thesis work, where a different data set was used for confidentiality reasons. Multiple methods (Hopkins method, ADONIS, ANOSIM, and Distance Regression) were used ...


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