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2019

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Articles 271 - 300 of 596

Full-Text Articles in Statistics and Probability

Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi May 2019

Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi

SMU Data Science Review

Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. …

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Machine Learning Vs Conventional Analysis Techniques For The Earth’S Magnetic Field Study, Sheri Loftin, Sarah J. Fite, Laura V. Bishop, Stavros Kotsiaros May 2019

Machine Learning Vs Conventional Analysis Techniques For The Earth’S Magnetic Field Study, Sheri Loftin, Sarah J. Fite, Laura V. Bishop, Stavros Kotsiaros

SMU Data Science Review

Abstract. Current techniques for calculating and generating models used for analyzing the Earth’s magnetic field are laborious and time-consuming. We assert that machine learning can have a significant impact on building magnetic field models more quickly and on various levels of complexity, specifically as it pertains to data cleansing and sorting. Our approach to this problem uses a reverse iterative multi-phase process for data cleansing, in which, initially, the CHAOS-6 model data is examined to determine if machine learning can be used to differentiate between useful data components for spherical harmonics, versus data noise. During this phase, six different machine …

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Leveraging Natural Language Processing Applications And Microblogging Platform For Increased Transparency In Crisis Areas, Ernesto Carrera-Ruvalcaba, Johnson Ekedum, Austin Hancock, Ben Brock May 2019

Leveraging Natural Language Processing Applications And Microblogging Platform For Increased Transparency In Crisis Areas, Ernesto Carrera-Ruvalcaba, Johnson Ekedum, Austin Hancock, Ben Brock

SMU Data Science Review

Through microblogging applications, such as Twitter, people actively document their lives even in times of natural disasters such as hurricanes and earthquakes. While first responders and crisis-teams are able to help people who call 911, or arrive at a designated shelter, there are vast amounts of information being exchanged online via Twitter that provide real-time, location-based alerts that are going unnoticed. To effectively use this information, the Tweets must be verified for authenticity and categorized to ensure that the proper authorities can be alerted. In this paper, we create a Crisis Message Corpus from geotagged Tweets occurring during 7 hurricanes …

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Tidying And Analysis Of The 2014 Texas English Ii End-Of-Course Exam, David Churchman, Abigail Morton Garland May 2019

Tidying And Analysis Of The 2014 Texas English Ii End-Of-Course Exam, David Churchman, Abigail Morton Garland

SMU Data Science Review

The state of Texas requires all public high school students to take End of Course (EOC) exams. The results of these exams are made nominally public, but in a shape and format that precludes ready analysis. To the extent possible, principles of tidy data will be applied to clean and analyze the publicly released data file for the 2014 English II EOC exam, providing insights into the EOC program and a case for better public data from the Texas Education Administration (TEA).

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A Mathematical Investigation On Tumor-Immune Dynamics: The Impact Of Vaccines On The Immune Response, Jonathan Quinonez, Neethi Dasu, Mahboobi Qureshi May 2019

A Mathematical Investigation On Tumor-Immune Dynamics: The Impact Of Vaccines On The Immune Response, Jonathan Quinonez, Neethi Dasu, Mahboobi Qureshi

Rowan-Virtua Research Day

Mathematical models analyzing tumor-immune interactions provide a framework by which to address specific scenarios in regard to tumor-immune dynamics. Important aspects of tumor-immune surveillance to consider is the elimination of tumor cells from a host’s cell-mediated immunity as well as the implications of vaccines derived from synthetic antigen. In present studies, our mathematical model examined the role of synthetic antigen to the strength of the immune system. The constructed model takes into account accepted knowledge of immune function as well as prior work done by de Pillis et al. All equations describing tumor-immune growth, antigen presentation, immune response, and interaction …

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Development Of A School Boredom Proneness Scale For Children, Taylor Carrington May 2019

Development Of A School Boredom Proneness Scale For Children, Taylor Carrington

Educational Specialist, 2009-2019

One common phrase heard from students is, “I’m bored.” However, there is no real understanding of what this actually means. In this study, elementary-age students were asked to respond to a newly developed School Boredom Proneness Scale (SBPS) including questions relating to a five-factor model of boredom. Students were also asked to rate how often they become bored at school and how bored they seem compared to classmates. In addition to student responses, parents and teachers were asked to rate how bored they thought the student was, and teachers were additionally asked to rate students’ level of work completion. The …

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Do Metabolic Networks Follow A Power Law? A Psamm Analysis, Ryan Geib, Lubos Thoma, Ying Zhang May 2019

Do Metabolic Networks Follow A Power Law? A Psamm Analysis, Ryan Geib, Lubos Thoma, Ying Zhang

Senior Honors Projects

Inspired by the landmark paper “Emergence of Scaling in Random Networks” by Barabási and Albert, the field of network science has focused heavily on the power law distribution in recent years. This distribution has been used to model everything from the popularity of sites on the World Wide Web to the number of citations received on a scientific paper. The feature of this distribution is highlighted by the fact that many nodes (websites or papers) have few connections (internet links or citations) while few “hubs” are connected to many nodes. These properties lead to two very important observed effects: the …

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Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark May 2019

Predictive Distributions Via Filtered Historical Simulation For Financial Risk Management, Tyson Clark

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

Filtered historical simulation with an underlying GARCH process can be used as a valuable tool in VaR analysis, as it derives risk estimates that are sensitive to the distributional properties of the historical data of the produced predictive density. I examine the applications to risk analysis that filtered historical simulation can provide, as well as an interpretation of the predictive density as a poor man’s Bayesian posterior distribution. The predictive density allows us to make associated probabilistic statements regarding the results for VaR analysis, giving greater measurement of risk and the ability to maintain the optimal level of risk per …

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Tdp-43 Proteinopathy In Aging: Associations With Risk-Associated Gene Variants And With Brain Parenchymal Thyroid Hormone Levels, Peter T. Nelson, Zsombor Gal, Wang-Xia Wang, Dana M. Niedowicz, Sergey C. Artiushin, Samuel Wycoff, Angela Wei, Gregory A. Jicha, David W. Fardo May 2019

Tdp-43 Proteinopathy In Aging: Associations With Risk-Associated Gene Variants And With Brain Parenchymal Thyroid Hormone Levels, Peter T. Nelson, Zsombor Gal, Wang-Xia Wang, Dana M. Niedowicz, Sergey C. Artiushin, Samuel Wycoff, Angela Wei, Gregory A. Jicha, David W. Fardo

Pathology and Laboratory Medicine Faculty Publications

TDP-43 proteinopathy is very prevalent among the elderly (affecting at least 25% of individuals over 85 years of age) and is associated with substantial cognitive impairment. Risk factors implicated in age-related TDP-43 proteinopathy include commonly inherited gene variants, comorbid Alzheimer's disease pathology, and thyroid hormone dysfunction. To test parameters that are associated with aging-related TDP-43 pathology, we performed exploratory analyses of pathologic, genetic, and biochemical data derived from research volunteers in the University of Kentucky Alzheimer's Disease Center autopsy cohort (n = 136 subjects). Digital pathologic methods were used to discriminate and quantify both neuritic and intracytoplasmic TDP-43 pathology …

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Understanding Water Consumption And Energy Trends In New York City, Wen Yong Huang, Johann Thiel May 2019

Understanding Water Consumption And Energy Trends In New York City, Wen Yong Huang, Johann Thiel

Publications and Research

In this study, we will be using the NYC Open Data website to examine publicly available data sets on water and energy consumption in New York City. In particular, we will use various scientific programming and machine learning modules in Python to analyze and visualize trends in water and energy usage within the five boroughs.

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Sampling Studies For Longitudinal Functional Data, Toni Jassel May 2019

Sampling Studies For Longitudinal Functional Data, Toni Jassel

Theses, Dissertations and Culminating Projects

We study the data setting consisting of functional data sets repeatedly observed over time. The focus is on the dynamic prediction of the future trajectory for a subject. Regression methods based on dynamic functional models are used for dynamic prediction of individual trajectories. We propose strategies for the selection of the study sampling design in the context of longitudinal functional data. An application to simulated child growth data is presented. The height-for-age z-score (HAZ) was the response variable in the functional dynamic models for prediction. The intent was to recommend four months for removal in our initial historic data set. …

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Statistical Modeling Of Count Data With Over-Dispersion Or Zero-Inflation Problems, Chengxin Zhang May 2019

Statistical Modeling Of Count Data With Over-Dispersion Or Zero-Inflation Problems, Chengxin Zhang

Theses, Dissertations and Culminating Projects

In this study, we will analyze a supply retailing company’s data to model the relationship between their customer’s past purchase behavior to predict their future online purchase behavior. The data was divided into time periods from 2016: P1-P6(January 31st to July 30th) and P7(July 31st to August 27th ). Based on customer’s past purchase information from the P1-P6 period, such as money spent, number of cart additions, transactions type, number of unique purchase dates, number of unique purchase skus, number of page views, number browse dates, company size, and number of products purchased, we aim to find if these information …

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What Can We Do? Puzzling Over The Interpretation Of Heredity And Variation From Galton To Genetic Engineering, Peter J. Taylor May 2019

What Can We Do? Puzzling Over The Interpretation Of Heredity And Variation From Galton To Genetic Engineering, Peter J. Taylor

Working Papers on Science in a Changing World

First six chapters of a book motivated as follows: When I had mentioned to colleagues that I was exploring some significant issues overlooked by both sides in nature-nurture debates, the typical response was “we know, of course, that nature and nurture are intertwined”; they never asked “which nature-nurture science are you referring to?” It occurred to me that, in the long history of nature-nurture debates, opposing sides had always assumed or implied that these different scientific approaches were speaking to the same issues. If that were the case, then the challenge—something I was already puzzling over—was how best to draw …

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A Bayesian Framework For Estimating Seismic Wave Arrival Time, Hua Zhong May 2019

A Bayesian Framework For Estimating Seismic Wave Arrival Time, Hua Zhong

Graduate Theses and Dissertations

Because earthquakes have a large impact on human society, statistical methods for better studying earthquakes are required. One characteristic of earthquakes is the arrival time of seismic waves at a seismic signal sensor. Once we can estimate the earthquake arrival time accurately, the earthquake location can be triangulated, and assistance can be sent to that area correctly. This study presents a Bayesian framework to predict the arrival time of seismic waves with associated uncertainty. We use a change point framework to model the different conditions before and after the seismic wave arrives. To evaluate the performance of the model, we …

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Comparing Elo, Glicko, Irt, And Bayesian Irt Statistical Models For Educational And Gaming Data, Breanna Morrison May 2019

Comparing Elo, Glicko, Irt, And Bayesian Irt Statistical Models For Educational And Gaming Data, Breanna Morrison

Graduate Theses and Dissertations

Statistical models used for estimating skill or ability levels often vary by field, however their underlying mathematical models can be very similar. Differences in the underlying models can be due to the need to accommodate data with different underlying formats and structure. As the models from varying fields increase in complexity, their ability to be applied to different types of data may have the ability to increase. Models that are applied to educational or psychological data have advanced to accommodate a wide range of data formats, including increased estimation accuracy with sparsely populated data matrices. Conversely, the field of online …

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Feasibility Of Multi-Year Forecast For The Colorado River Water Supply: Time Series Modeling, Brian Plucinski May 2019

Feasibility Of Multi-Year Forecast For The Colorado River Water Supply: Time Series Modeling, Brian Plucinski

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

The Colorado River is one of the largest resources for water in the United States, as well as being an important asset to the economy. Previous studies have shown a connection between the Great Salt Lake and the Colorado River. This study used time series analysis to build models to predict the water supply of the Colorado River ten years out. These models used data from the Colorado River in addition to Great Salt Lake water elevation. Several models suggest a decline in water supply from 2013 – 2020, before starting to increase. These predictions differ from predictions published by …

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Do Misperceptions Of Peer Drinking Influence Personal Drinking Behavior? Results From A Complete Social Network Of First-Year College Students, Melissa J. Cox, Angelo M. Dibello, Matthew K. Meisel, Miles Q. Ott, Shannon R. Kenney, Melissa A. Clark, Nancy P. Barnett May 2019

Do Misperceptions Of Peer Drinking Influence Personal Drinking Behavior? Results From A Complete Social Network Of First-Year College Students, Melissa J. Cox, Angelo M. Dibello, Matthew K. Meisel, Miles Q. Ott, Shannon R. Kenney, Melissa A. Clark, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

This study considered the influence of misperceptions of typical versus self-identified important peers' heavy drinking on personal heavy drinking intentions and frequency utilizing data from a complete social network of college students. The study sample included data from 1,313 students (44% male, 57% White, 15% Hispanic/Latinx) collected during the fall and spring semesters of their freshman year. Students provided perceived heavy drinking frequency for a typical student peer and up to 10 identified important peers. Personal past-month heavy drinking frequency was assessed for all participants at both time points. By comparing actual with perceived heavy drinking frequencies, measures of misperceptions …

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A Systematic Assessment Of Socio-Economic Impacts Of Prolonged Episodic Volcano Crises, Justin Peers May 2019

A Systematic Assessment Of Socio-Economic Impacts Of Prolonged Episodic Volcano Crises, Justin Peers

Electronic Theses and Dissertations

Uncertainty surrounding volcanic activity can lead to socio-economic crises with or without an eruption as demonstrated by the post-1978 response to unrest of Long Valley Caldera (LVC), CA. Extensive research in physical sciences provides a foundation on which to assess direct impacts of hazards, but fewer resources have been dedicated towards understanding human responses to volcanic risk. To evaluate natural hazard risk issues at LVC, a multi-hazard, mail-based, household survey was conducted to compare perceptions of volcanic, seismic, and wildfire hazards. Impacts of volcanic activity on housing prices and businesses were examined at the county-level for three volcanoes with a …

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Raman And Surface Enhanced Raman Spectroscopy For Forensic Analysis: Case Studies On The Identification Of Illicit Substances And Artist Pigments, Abed Haddad May 2019

Raman And Surface Enhanced Raman Spectroscopy For Forensic Analysis: Case Studies On The Identification Of Illicit Substances And Artist Pigments, Abed Haddad

Dissertations, Theses, and Capstone Projects

Raman spectroscopy is an effective tool for detecting trace amounts of material by fingerprint-like vibrational spectra. At times, the weak intensity of Raman scattering can make it difficult to distinguish trace materials. This shortcoming is addressed by surface‐enhanced Raman spectroscopy (SERS), which produces strong signal enhancements when target compounds are near metal nanoparticles. For the first part of this thesis, the identification of fentanyl and carfentanil, main culprits in the opioid epidemic, was done using normal Raman and the SERS spectroscopy. As an aid in the assignment of the spectral lines, a computational model was built using Density Functional Theory …

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Comparison Of Imputation Methods For Mixed Data Missing At Random, Kaitlyn Heidt May 2019

Comparison Of Imputation Methods For Mixed Data Missing At Random, Kaitlyn Heidt

Electronic Theses and Dissertations

A statistician's job is to produce statistical models. When these models are precise and unbiased, we can relate them to new data appropriately. However, when data sets have missing values, assumptions to statistical methods are violated and produce biased results. The statistician's objective is to implement methods that produce unbiased and accurate results. Research in missing data is becoming popular as modern methods that produce unbiased and accurate results are emerging, such as MICE in R, a statistical software. Using real data, we compare four common imputation methods, in the MICE package in R, at different levels of missingness. The …

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Generalizations Of The Arcsine Distribution, Rebecca Rasnick May 2019

Generalizations Of The Arcsine Distribution, Rebecca Rasnick

Electronic Theses and Dissertations

The arcsine distribution looks at the fraction of time one player is winning in a fair coin toss game and has been studied for over a hundred years. There has been little further work on how the distribution changes when the coin tosses are not fair or when a player has already won the initial coin tosses or, equivalently, starts with a lead. This thesis will first cover a proof of the arcsine distribution. Then, we explore how the distribution changes when the coin the is unfair. Finally, we will explore the distribution when one person has won the first …

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Dynamic Attribute-Level Best Worst Discrete Choice Experiments, Amanda Working, Mohammed Alqawba, Norou Diawara May 2019

Dynamic Attribute-Level Best Worst Discrete Choice Experiments, Amanda Working, Mohammed Alqawba, Norou Diawara

Mathematics & Statistics Faculty Publications

Dynamic modelling of decision maker choice behavior of best and worst in discrete choice experiments (DCEs) has numerous applications. Such models are proposed under utility function of decision maker and are used in many areas including social sciences, health economics, transportation research, and health systems research. After reviewing references on the study of such experiments, we present example in DCE with emphasis on time dependent best-worst choice and discrimination between choice attributes. Numerical examples of the dynamic DCEs are simulated, and the associated expected utilities over time of the choice models are derived using Markov decision processes. The estimates are …

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Simulation As A Predictor In Probability, Xiaona Zhou May 2019

Simulation As A Predictor In Probability, Xiaona Zhou

Publications and Research

In this study, we simulate bivariate normal data. We gain intuition about the bivariate normal distribution by comparing the generated data to the associated bivariate normal density surface. We also get results about covariance and correlation. We will use tools from linear algebra to discuss transformations of random normal vectors, and the use of contours.

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A Comparison Of Standard Denoising Methods For Peptide Identification, Skylar Carpenter May 2019

A Comparison Of Standard Denoising Methods For Peptide Identification, Skylar Carpenter

Electronic Theses and Dissertations

Peptide identification using tandem mass spectrometry depends on matching the observed spectrum with the theoretical spectrum. The raw data from tandem mass spectrometry, however, is often not optimal because it may contain noise or measurement errors. Denoising this data can improve alignment between observed and theoretical spectra and reduce the number of peaks. The method used by Lewis et. al (2018) uses a combined constant and moving threshold to denoise spectra. We compare the effects of using the standard preprocessing methods baseline removal, wavelet smoothing, and binning on spectra with Lewis et. al’s threshold method. We consider individual methods and …

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Effects Of Perioperative Hyperglycemia In Patients With Diabetes Compared To Patients Without Diabetes: A Retrospective Study Of Treatment And Outcomes, Matthew Anderson May 2019

Effects Of Perioperative Hyperglycemia In Patients With Diabetes Compared To Patients Without Diabetes: A Retrospective Study Of Treatment And Outcomes, Matthew Anderson

Capstone Experience: Master of Public Health

The main goal of this project was to examine the differences in perioperative hyperglycemia treatment received by patients with a diagnosis of diabetes mellitus (DM) and patients without a diagnosis of diabetes (NDM); and how these treatment differences can affect the length of hospital stay. Studies have revealed that, when comparing DM and NDM patients with the same degree of perioperative hyperglycemia, NDM patients suffer worse outcomes. It has been suggested in previous research that this may be because NDM patients receive treatment that does not measure up to the standard of care treatment that DM patients receive. In this …

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An Analysis Of Postmastectomy Breast Reconstruction Due To Breast Cancer In Nevada And The United States From 2008-2013, Jenna Webb May 2019

An Analysis Of Postmastectomy Breast Reconstruction Due To Breast Cancer In Nevada And The United States From 2008-2013, Jenna Webb

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background: In the United States, female breast cancer was the leading cause of new cancer cases from 2011-2015. Since the Women’s Health and Cancer Act of 1998 (WHCRA), the federal government mandates employee and private health insurance providers to cover breast reconstruction if they cover mastectomies. Postmastectomy breast reconstruction (PBR) rates increased after the WHCRA, but these rates have remained relatively low throughout recent years. Objective: The objective of this study was to determine factors associated with women having PBR due to breast cancer in Nevada and the United States from 2008 to 2013. Methods: Using two HCUP database, NIS …

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Advanced Statistics In Arkansas Sports Reporting, Andrew Lee Epperson May 2019

Advanced Statistics In Arkansas Sports Reporting, Andrew Lee Epperson

Graduate Theses and Dissertations

This study seeks to analyze how Arkansas’ sports journalists are adapting to the recent surge in available advanced statistics that are being used by certain national news organizations. Using in-depth qualitative research that includes in-depth interviews with a number of individuals in the print, broadcast, and athletics side of sports coverage, we discover how journalists and coaches use these next-generation analytics, what they fundamentally mean for the evolution of each respective path, and why so few Arkansas reporters and writers use them at the time of this paper’s defense. We see how budgets and deadlines restrict the use of these …

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A Hidden Markov Factor Analysis Framework For Seizure Detection In Epilepsy Patients, Mahboubeh Madadi May 2019

A Hidden Markov Factor Analysis Framework For Seizure Detection In Epilepsy Patients, Mahboubeh Madadi

Graduate Theses and Dissertations

Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. Detection of seizure from the recorded EEG is a laborious, time consuming and expensive task. In this study, we propose an automated seizure detection framework to assist electroencephalographers and physicians with identification of seizures in recorded EEG signals. In addition, an automated seizure detection algorithm can be used for treatment through automatic intervention during the seizure activity and on time triggering of the injection of a radiotracer to …

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Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan May 2019

Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan

Faculty Publications

In this work we construct a Markov family of martingale solutions for 3D stochastic Navier–Stokes equations (SNSE) perturbed by Lévy noise with periodic boundary conditions. Using the Kolmogorov equations of integrodifferential type associated with the SNSE perturbed by Lévy noise, we construct a transition semigroup and establish the existence of a unique invariant measure. We also show that it is ergodic and strongly mixing.
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Telomeres, Nutrition And Mortality: Risk Factors For The Rate Of Telomere Length Decline And The Associations Between Telomere Length, Nutrition And Mortality, Saruna Ghimire May 2019

Telomeres, Nutrition And Mortality: Risk Factors For The Rate Of Telomere Length Decline And The Associations Between Telomere Length, Nutrition And Mortality, Saruna Ghimire

UNLV Theses, Dissertations, Professional Papers, and Capstones

Introduction: Telomeres are nucleoprotein structures located at the ends of eukaryotic chromosomes, thought to protect the DNA from damage. As a person experiences stressors, harmful exposures, and other diseases throughout their life, telomeres are thought to become damaged and their length shortened, decreasing their ability to protect the DNA. Nutrition is an important aspect of healthy aging. Preservation of telomere length (TL) is thought to be one of the mechanisms by which good nutrition can delay or prevent the development of chronic disease and death. Recent evidence of preservation of TL with good nutrition is promising. Thus, the aim of …

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