On The Analysis Of The Sir Epidemic Model For Small Networks: An Application In Hospital Settings, 2017 University of Leeds
On The Analysis Of The Sir Epidemic Model For Small Networks: An Application In Hospital Settings, Martin Lopez-Garcia
Biology and Medicine Through Mathematics Conference
No abstract provided.
Can Cone Signals In The Wild Be Predicted From The Past?, 2017 University of Manchester, UK
Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch
In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over ...
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 ...
Statistically Analyzing Assembly Line Processing Times Through Incorporation Of Product Variation, 2017 Murray State University
Statistically Analyzing Assembly Line Processing Times Through Incorporation Of Product Variation, Kyle Rehr, Matthew Farr
Timing methods and performance metrics are important in the heavily industrialized world we live in. Industrial plants use metrics to measure quality of production, help make decisions, and drive the strategy of the organization. However, there are many factors to be considered when measuring performance based on a metric; of which we will be analyzing the importance of product variation. We will be analyzing assembly line timings, whilst controlling for product variance, to show the importance differences between products makes in one’s ability to predict performance. In addition, we will be analyzing the current “statistical” methods used by an ...
2014 Reporting Of Sexual Assault: Institutional Comparisons, 2017 Cornell University
2014 Reporting Of Sexual Assault: Institutional Comparisons, M. E. Karns
Research Studies and Reports
Institutions of higher education are required to submit annual reports of sexual assault crimes to the Department of Education under the Clery Act. The Department of Education makes this data publicly available. Two primary measures are used to assess reporting of assault on campus: the Assault Reporting Ratio (ARR) and the Reporting Rate per 10,000 students (R10K). These measures are easily calculated and can be used to assess practices and policies that impact the reporting of sexual assault on campus.
The ARR and R10K are rate comparisons, a method widely used in public health. These rate comparisons measure how ...
Perennial Warm-Season Grasses For Producing Biofuel And Enhancing Soil Properties: An Alternative To Corn Residue Removal, 2017 University of Nebraska-Lincoln
Perennial Warm-Season Grasses For Producing Biofuel And Enhancing Soil Properties: An Alternative To Corn Residue Removal, Humberto Blanco-Canqui, Robert B. Mitchell, Virginia L. Jin, Marty R. Schmer, Kent M. Eskridge
Faculty Publications, Department of Statistics
Removal of corn (Zea mays L.) residues at high rates for biofuel and other off-farm uses may negatively impact soil and the environment in the long term. Biomass removal from perennial warm-season grasses (WSGs) grown in marginally-productive lands could be an alternative to corn residue removal as biofuel feedstocks while controlling water and wind erosion, sequestering carbon (C), cycling water and nutrients, and enhancing other soil ecosystem services. We compared wind and water erosion potential, soil compaction, soil hydraulic properties, soil organic C (SOC), and soil fertility between biomass removal from WSGs and corn residue removal from rainfed no-till continuous ...
Impact Of Menthol Smoking On Nicotine Dependence For Diverse Racial/Ethnic Groups Of Daily Smokers, 2017 University of Central Florida
Impact Of Menthol Smoking On Nicotine Dependence For Diverse Racial/Ethnic Groups Of Daily Smokers, Julia N. Soulakova, Ryan R. Danczak
Faculty Publications, Department of Statistics
Introduction: The aims of this study were to evaluate whether menthol smoking and race/ethnicity are associated with nicotine dependence in daily smokers. Methods: The study used two subsamples of U.S. daily smokers who responded to the 2010–2011 Tobacco Use Supplement to the Current Population Survey. The larger subsample consisted of 18,849 non-Hispanic White (NHW), non-Hispanic Black (NHB), and Hispanic (HISP) smokers. The smaller subsample consisted of 1112 non-Hispanic American Indian/Alaska Native (AIAN), non-Hispanic Asian (ASIAN), non-Hispanic Hawaiian/Pacific Islander (HPI), and non-Hispanic Multiracial (MULT) smokers. Results: For larger (smaller) groups the rates were 45% (33 ...
Detecting Discordance Enrichment Among A Series Of Two-Sample Genome-Wide Expression Data Sets, 2017 George Washington University
Detecting Discordance Enrichment Among A Series Of Two-Sample Genome-Wide Expression Data Sets, Yinglei Lai, Fanni Zhang, Tapan Nayak, Reza Modarres, Norman H. Lee, Timothy A. Mccaffrey
Epidemiology and Biostatistics Faculty Publications
With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest.
In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when ...
Tutorial For Using The Center For High Performance Computing At The University Of Utah And An Example Using Random Forest, Stephen Barton
All Graduate Plan B and other Reports
Random Forests are very memory intensive machine learning algorithms and most computers would fail at building models from datasets with millions of observations. Using the Center for High Performance Computing (CHPC) at the University of Utah and an airline on-time arrival dataset with 7 million observations from the U.S. Department of Transportation Bureau of Transportation Statistics we built 316 models by adjusting the depth of the trees and randomness of each forest and compared the accuracy and time each took. Using this dataset we discovered that substantial restrictions to the size of trees, observations allowed for each tree, and ...
A Traders Guide To The Predictive Universe- A Model For Predicting Oil Price Targets And Trading On Them, 2016 Washington University in St. Louis
A Traders Guide To The Predictive Universe- A Model For Predicting Oil Price Targets And Trading On Them, Jimmie Harold Lenz
Doctor of Business Administration Dissertations
At heart every trader loves volatility; this is where return on investment comes from, this is what drives the proverbial “positive alpha.” As a trader, understanding the probabilities related to the volatility of prices is key, however if you could also predict future prices with reliability the world would be your oyster. To this end, I have achieved three goals with this dissertation, to develop a model to predict future short term prices (direction and magnitude), to effectively test this by generating consistent profits utilizing a trading model developed for this purpose, and to write a paper that anyone with ...
Performance-Constrained Binary Classification Using Ensemble Learning: An Application To Cost-Efficient Targeted Prep Strategies, 2016 Division of Biostatistics, School of Public Health, University of California, Berkeley
Performance-Constrained Binary Classification Using Ensemble Learning: An Application To Cost-Efficient Targeted Prep Strategies, Wenjing Zheng, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
Binary classifications problems are ubiquitous in health and social science applications. In many cases, one wishes to balance two conflicting criteria for an optimal binary classifier. For instance, in resource-limited settings, an HIV prevention program based on offering Pre-Exposure Prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program to deliver. In this article, we consider a general class of performance-constrained binary classification problems wherein the objective function and the ...
Optimal Design Of Low-Density Snp Arrays For Genomic Prediction: Algorithm And Applications, 2016 GeneSeek (a Neogen Company)
Optimal Design Of Low-Density Snp Arrays For Genomic Prediction: Algorithm And Applications, Xiao-Lin Wu, Jiaqi Xu, Guofei Feng, George R. Wiggans, Jeremy F. Taylor, Jun He, Changsong Qian, Jiansheng Qiu, Barry Simpson, Jeremy Walker, Stewart Bauck
Faculty Publications, Department of Statistics
Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution ...
Probabilistic Methods In Information Theory, 2016 Cal State University-San Bernardino
Probabilistic Methods In Information Theory, Erik W. Pachas
Electronic Theses, Projects, and Dissertations
Given a probability space, we analyze the uncertainty, that is, the amount of information of a finite system, by studying the entropy of the system. We also extend the concept of entropy to a dynamical system by introducing a measure preserving transformation on a probability space. After showing some theorems and applications of entropy theory, we study the concept of ergodicity, which helps us to further analyze the information of the system.
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, 2016 Purdue University
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
The Summer Undergraduate Research Fellowship (SURF) Symposium
Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that ...
Dangerous Liaisons An Endogenous Model Of International Trade And Human Rights, 2016 Iowa State University
Dangerous Liaisons An Endogenous Model Of International Trade And Human Rights, Olga Chyzh
This article applies recent advances in network analysis to highlight a central tension faced by policymakers – balancing the benefits of engaging with the international system and the associated domestic policy costs. International trade rewards certain domestic practices, such as respect for human rights. Enforcing such practices, however, is politically costly and sometimes prohibitive to state leaders who rely on political repression to stay in power. In such cases, domestic elites often resort to an alternative strategy of securing the benefits of international trade – setting up indirect trade channels through intermediary states. These competing incentives are modeled within a single framework ...
Keeping Up With Which Joneses: Spatial Diffusion Of Rule Of Law Through Economic International Organizations, 2016 Iowa State University
Keeping Up With Which Joneses: Spatial Diffusion Of Rule Of Law Through Economic International Organizations, Olga Chyzh
I develop a theory of spatial diffusion of the rule of law, where “space” is conceptualized as shared memberships in economic international organizations (IOs). I argue that the rule of law diffuses as a result of economic competition and socialization. Outside evaluators, such as international leaders, activists, and most importantly, international firms and investors, often assess states’ attractiveness as a business venue by comparing them to similar states. The natural reference group for such comparisons is not just geographical neighbors, but also states with shared memberships in economic IOs. Responding to this evaluation, states identify members of their own reference ...
Well I'Ll Be Damned - Insights Into Predictive Value Of Pedigree Information In Horse Racing, 2016 University of Southampton
Well I'Ll Be Damned - Insights Into Predictive Value Of Pedigree Information In Horse Racing, Timothy Baker Mr, Ming-Chien Sung, Johnnie Johnson Professor, Tiejun Ma
International Conference on Gambling and Risk Taking
Fundamental form characteristics like how fast a horse ran at its last start, are widely used to help predict the outcome of horse racing events. The exception being in races where horses haven’t previously competed, such as Maiden races, where there is little or no publicly available past performance information. In these types of events bettors need only consider a simplified suite of factors however this is offset by a higher level of uncertainty. This paper examines the inherent information content embedded within a horse’s ancestry and the extent to which this information is discounted in the United ...
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, 2016 Washington University in St. Louis
Spot Volatility Estimation Of Ito Semimartingales Using Delta Sequences, Weixuan Gao
Arts & Sciences Electronic Theses and Dissertations
This thesis studies a unifying class of nonparametric spot volatility estimators proposed by Mancini et. al.(2013). This method is based on delta sequences and is conceived to include many of the existing estimators in the field as special cases. The thesis first surveys the asymptotic theory of the proposed estimators under an infill asymptotic scheme and fixed time horizon, when the state variable follows a Brownian semimartingale. Then, some extensions to include jumps and financial microstructure noise in the observed price process are also presented. The main goal of the thesis is to assess the suitability of the proposed ...
Takens Theorem With Singular Spectrum Analysis Applied To Noisy Time Series, 2016 East Tennessee State University
Takens Theorem With Singular Spectrum Analysis Applied To Noisy Time Series, Thomas K. Torku
Electronic Theses and Dissertations
The evolution of big data has led to financial time series becoming increasingly complex, noisy, non-stationary and nonlinear. Takens theorem can be used to analyze and forecast nonlinear time series, but even small amounts of noise can hopelessly corrupt a Takens approach. In contrast, Singular Spectrum Analysis is an excellent tool for both forecasting and noise reduction. Fortunately, it is possible to combine the Takens approach with Singular Spectrum analysis (SSA), and in fact, estimation of key parameters in Takens theorem is performed with Singular Spectrum Analysis. In this thesis, we combine the denoising abilities of SSA with the Takens ...
Flesch-Kincaid Reading Grade Level Re-Examined: Creating A Uniform Method For Calculating Readability On A Certification Exam, 2016 Southern Illinois University Carbondale
Flesch-Kincaid Reading Grade Level Re-Examined: Creating A Uniform Method For Calculating Readability On A Certification Exam, Emily Neuhoff, Kristiana M. Feeser, Kayla Sutherland, Thomas Hovatter
Online Journal for Workforce Education and Development
Objective: This study attempted to establish a consistent measurement technique of the readability of a state-wide Certified Nursing Assistant’s (CNA) certification exam. Background: Monitoring the readability level of an exam helps ensure all test versions do not exceed the maximum reading level of the exam, and that knowledge of the subject matter, rather than reading ability, is being assessed. Method: A two part approach was used to specify and evaluate readability. First, two methods (Microsoft Word® (MSW) software and published readability formulae) were used to calculate Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKRGL) for multiple ...