Applied Statistics Commons^™

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.

[email protected]

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 call data, and faculty …

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 …

Using Mountain Snowpack To Predict Summer Water Availability In Semiarid Mountain Watersheds, Rebecca Dawn Garst

Boise State University Theses and Dissertations

In the mountainous landscapes of the western United States, water resources are dominated by snowpack. As temperatures rise in spring and summer, the melting snow produces an increase in river flow levels. Reservoirs are used during this increase to retain surplus water, which is released to supplement growing season water supply once the peak flows decrease to below water demands. Once there is no longer surplus natural flow of water, the water accounting changes – referred to as the day of allocation (DOA), and water previously retained within the reservoir is used to supplement the lower flow levels. The amount …

Environmentally-Driven Variation In The Population Dynamics Of Gulf Menhaden (Brevoortia Patronus), Grant D. Adams

Master's Theses

Gulf Menhaden (Brevoortia patronus) is an abundant forage fish distributed throughout the Northern Gulf of Mexico (NGOM). Gulf Menhaden support the second largest fishery, by weight, in the United States and represent a key linkage between upper and lower trophic levels. Variation in the population dynamics can, therefore, pose consequences for the ecology and economy in the NGOM. Here we aim to understand variation in the individual and population dynamics of Gulf Menhaden throughout ontogeny and how such variation relates to environmental processes. We utilized a suite of fishery-dependent and –independent, remote sensing, modeled, and in situ data …

A Cross-Sectional Exploration Of Household Financial Reactions And Homebuyer Awareness Of Registered Sex Offenders In A Rural, Suburban, And Urban County., John Charles Navarro

Electronic Theses and Dissertations

As stigmatized persons, registered sex offenders betoken instability in communities. Depressed home sale values are associated with the presence of registered sex offenders even though the public is largely unaware of the presence of registered sex offenders. Using a spatial multilevel approach, the current study examines the role registered sex offenders influence sale values of homes sold in 2015 for three U.S. counties (rural, suburban, and urban) located in Illinois and Kentucky within the social disorganization framework. Homebuyers were surveyed to examine whether awareness of local registered sex offenders and the homebuyer’s community type operate as moderators between home selling …

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

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

While internal and external unbonded tendons are widely utilized in concrete structures, the analytic solution for the increase in unbonded tendon stress, Δ���, 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 Δ��� are made via Principal Component Regression models, and the method …

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

Published and 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 models with …

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.

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

Mahurin 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

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 to receive …

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

Computer Science and Software Engineering

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.

Understanding Angiography-Based Aneurysm Flow Fields Through Comparison With Computational Fluid Dynamics, Juan R. Cebral, F. Mut, Bong Jae Chung, L. Spelle, J. Moret, F. Van Nijnatten, D. Ruijters

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

BACKGROUND AND PURPOSE: Hemodynamics is thought to be an important factor for aneurysm progression and rupture. Our aim was to evaluate whether flow fields reconstructed from dynamic angiography data can be used to realistically represent the main flow structures in intracranial aneurysms. MATERIALS AND METHODS: DSA-based flow reconstructions, obtained during interventional treatment, were compared qualitatively with flow fields obtained from patient-specific computational fluid dynamics models and quantitatively with projections of the computational fluid dynamics fields (by computing a directional similarity of the vector fields) in 15 cerebral aneurysms. RESULTS: The average similarity between the DSA and the projected computational fluid …

The Mosaic Package: Helping Students To 'Think With Data' Using R, Randall J. Pruim, Daniel T. Kaplan, Nicholas J. Horton

University Faculty Publications and Creative Works

The mosaic package provides a simplified and systematic introduction to the core functionality related to descriptive statistics, visualization, modeling, and simulation-based inference required in first and second courses in statistics. This introduction to the package describes some of the guiding principles behind the design of the package and provides illustrative examples of several of the most important functions it implements. These can be combined to help students "think with data" using R in their early course work, starting with simple, yet powerful, declarative commands.

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

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

Biology and Medicine Through Mathematics Conference

No abstract provided.

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 …

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

Student Scholar Symposium 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 …

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

Student Scholar Symposium 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 …

Using Multiple Imputation To Address Missing Values Of Hierarchical Data, Yujia Zhang, Sara Crawford, Sheree Boulet, Michael Monsour, Bruce Cohen, Patricia Mckane, Karen Freeman

Journal of Modern Applied Statistical Methods

Missing data may be a concern for data analysis. If it has a hierarchical or nested structure, the SUDAAN package can be used for multiple imputation. This is illustrated with birth certificate data that was linked to the Centers for Disease Control and Prevention’s National Assisted Reproductive Technology Surveillance System database. The Cox-Iannacchione weighted sequential hot deck method was used to conduct multiple imputation for missing/unknown values of covariates in a logistic model.

Selection Of Statistical Software For Data Scientists And Teachers, Ceyhun Ozgur, Min Dou, Yang Li, Grace Rogers

Journal of Modern Applied Statistical Methods

The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software sought by employers and to align this with the software taught by universities. This paper will examine multiple data analysis software – Excel add-ins, SPSS, SAS, Minitab, and R – and it will outline the cost, training, statistical methods/tests/uses, and specific uses within industry for each of these software. It will further explain implications for universities and students.

An Unbiased Estimator Of The Greatest Lower Bound, Nol Bendermacher

Journal of Modern Applied Statistical Methods

The greatest lower bound to the reliability of a test, based on a single administration, is the Greatest Lower Bound (GLB). However the estimate is seriously biased. An algorithm is described that corrects this bias.

Monte Carlo Study Of Some Classification-Based Ridge Parameter Estimators, Adewale Folaranmi Lukman, Kayode Ayinde, Adegoke S. Ajiboye

Journal of Modern Applied Statistical Methods

Ridge estimator in linear regression model requires a ridge parameter, K, of which many have been proposed. In this study, estimators based on Dorugade (2014) and Adnan et al. (2014) were classified into different forms and various types using the idea of Lukman and Ayinde (2015). Some new ridge estimators were proposed. Results shows that the proposed estimators based on Adnan et al. (2014) perform generally better than the existing ones.

Multivariate Multilevel Modeling Of Age Related Diseases, Kapuruge N. O. Ranathunga, Roshini Sooriyarachchi

Journal of Modern Applied Statistical Methods

The emerging role of modeling multivariate multilevel data in the context of analyzing the risk factors are examined for the severity of cardiovascular disease diabetes, and chronic respiratory conditions. The modeling phase results leads to some important interaction terms between blood glucose, blood pressure, obesity, smoking and alcohol to the mortality rates.

Analysis Of Robust Parameter Designs, Tak K. Mak, Fassil Nebebe

Journal of Modern Applied Statistical Methods

The analysis of robust parameter design is discussed via a model incorporating mean-variance relationship which, when ignored as in the classical regression approach, can be problematic. The model is also capable of alleviating the difficulties of the regression approach in the search of the minimum variance occurring region.

Distribution Fits For Various Parameters In The Florida Public Hurricane Loss Model, Victoria Oxenyuk, Sneh Gulati, B. M. Golam Kibria, Shahid Hamid

Journal of Modern Applied Statistical Methods

The purpose of this study is to re-analyze the atmospheric science component of the Florida Public Hurricane Loss Model v. 5.0, in order to investigate if the distributional fits used for the model parameters could be improved upon. We consider alternate fits for annual hurricane occurrence, radius of maximum winds and the pressure profile parameter.

Stochastic Model For Cancer Cell Growth Through Single Forward Mutation, Jayabharathiraj Jayabalan

Journal of Modern Applied Statistical Methods

A stochastic model for cancer cell growth in any organ is presented, based on a single forward mutation. Cell growth is explained in a one-dimensional stochastic model, and statistical measures for the variable representing the number of malignant cells are derived. A numerical study is conducted to observe the behavior of the model.

Genetic Algorithms For Cross-Calibration Of Categorical Data, Suja M. Aboukhamseen, Rym A. M'Hallah

Journal of Modern Applied Statistical Methods

The probabilistic problem of cross-calibration of two categorical variables is addressed. A probabilistic forecast of the categorical variables is obtained based on a sample of observed data. This forecast is the output of a genetic algorithm based approach, which makes no assumption on the type of relationship between the two variables and applies a scoring rule to assess the fitness of the chromosomes. It converges to a good-quality point probability forecast of the joint distribution of the two variables. The proposed approach is applied both at stationary points in time and across time. Its performance is enhanced when additional sampled …

A Schmid-Leiman-Based Transformation Resulting In Perfect Inter-Correlations Of Three Types Of Factor Score Predictors, André Beauducel

Journal of Modern Applied Statistical Methods

Factor score predictors are computed when individual factor scores are of interest. Conditions for a perfect inter-correlation of the best linear factor score predictor, the best linear conditionally unbiased predictor, and the determinant best linear correlation-preserving predictor are presented. A transformation resulting in perfect correlations of the three predictors is proposed.