Macrobenthic Communities In The Northern Gulf Of Mexico Hypoxic Zone: Testing The Pearson-Rosenberg Model, 2015 The University of Southern Mississippi
Macrobenthic Communities In The Northern Gulf Of Mexico Hypoxic Zone: Testing The Pearson-Rosenberg Model, Shivakumar Shivarudrappa
The Pearson and Rosenberg (P-R) conceptual model of macrobenthic succession was used to assess the impact of hypoxia (dissolved oxygen [DO] ≤ 2 mg/L) on the macrobenthic community on the continental shelf of northern Gulf of Mexico for the first time. The model uses a stress-response relationship between environmental parameters and the macrobenthic community to determine the ecological condition of the benthic habitat. The ecological significance of dissolved oxygen in a benthic habitat is well understood. In addition, the annual recurrence of bottom-water hypoxia on the Louisiana/Texas shelf during summer months is well documented.
The P-R model illustrates the ...
A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, 2015 University of Southern Mississippi
A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, Andreas Moshogianis
Hypoxia events occur when dissolved oxygen concentrations fall below the minimum threshold (dissolved oxygen concentrations < 2 mg O2 L-1) necessary to avoid respiratory distress among aquatic organisms. In the Mississippi Sound and Bight, hypoxia is most prevalent from late-spring through late summer. Since hypoxia events can have dramatic effects on coastal fisheries, the spatial and temporal magnitude of hypoxia presents a clear threat to the productive fisheries in the northern Gulf of Mexico. Long-term hydrographic data were collected from eight sampling stations on a monthly basis from January 2009 to December 2011 along a cross-shelf transect from the mouth of Bay ...
Predicting Intraday Financial Market Dynamics Using Takens' Vectors; Incorporating Causality Testing And Machine Learning Techniques, 2015 East Tennessee State University
Predicting Intraday Financial Market Dynamics Using Takens' Vectors; Incorporating Causality Testing And Machine Learning Techniques, Abubakar-Sadiq Bouda Abdulai
Electronic Theses and Dissertations
Traditional approaches to predicting financial market dynamics tend to be linear and stationary, whereas financial time series data is increasingly nonlinear and non-stationary. Lately, advances in dynamical systems theory have enabled the extraction of complex dynamics from time series data. These developments include theory of time delay embedding and phase space reconstruction of dynamical systems from a scalar time series. In this thesis, a time delay embedding approach for predicting intraday stock or stock index movement is developed. The approach combines methods of nonlinear time series analysis with those of causality testing, theory of dynamical systems and machine learning (artificial ...
A Localized Approach To The Origins Of Pottery In Upper Mesopotamia, 2015 University of Toronto
A Localized Approach To The Origins Of Pottery In Upper Mesopotamia, Elizabeth Gibbon
Laurier Undergraduate Journal of the Arts
No abstract provided.
Hilbe-Pglr-Errata-And-Comments, 2015 Arizona State University
Hilbe-Pglr-Errata-And-Comments, Joseph M. Hilbe
Joseph M Hilbe
Errata and Comments for Practical Guide to Logistic Regression
Addition To Pglr Chap 6, 2015 Arizona State University
Addition To Pglr Chap 6, Joseph M. Hilbe
Joseph M Hilbe
Addition to Chapter 6 in Practical Guide to Logistic Regression. Added section on Bayesian logistic regression using Stata.
Meta-Analysis Of Genome-Wide Association Studies With Correlated Individuals: Application To The Hispanic Community Health Study/Study Of Latinos (Hchs/Sol), Tamar Sofer, John R. Shaffer, Misa Graff, Qibin Qi, Adrienne M. Stilp, Stephanie M. Gogarten, Kari E. North, Carmen R. Isasi, Cathy C. Laurie, Adam A. Szpiro
UW Biostatistics Working Paper Series
Investigators often meta-analyze multiple genome-wide association studies (GWASs) to increase the power to detect associations of single nucleotide polymorphisms (SNPs) with a trait. Meta-analysis is also performed within a single cohort that is stratified by, e.g., sex or ancestry group. Having correlated individuals among the strata may complicate meta-analyses, limit power, and inflate Type 1 error. For example, in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), sources of correlation include genetic relatedness, shared household, and shared community. We propose a novel mixed-effect model for meta-analysis, “MetaCor", which accounts for correlation between stratum-specific effect estimates. Simulations show ...
Bayes Multiple Binary Classifier - How To Make Decisions Like A Bayesian, 2015 Florida International University
Bayes Multiple Binary Classifier - How To Make Decisions Like A Bayesian, Wensong Wu
Mathematics Colloquium Series
This presentation will start by a general introduction of Bayesian statistics, which has become popular in the era of big data. Then we consider a two-class classification problem, where the goal is to predict the class membership of M units based on the values of high-dimensional categorical predictor variables as well as both the values of predictor variables and the class membership of other N independent units. We focus on applying generalized linear regression models with Boolean expressions of categorical predictors. We consider a Bayesian and decision-theoretic framework, and develop a general form of Bayes multiple binary classification functions with ...
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, 2015 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, Zhenke Wu, Maria Deloria-Knoll, Scott L. Zeger
Johns Hopkins University, Dept. of Biostatistics Working Papers
The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable. The paper describes a latent variable model designed to infer from case-control data the etiology distribution for the population of cases, and for an individual case given his or her measurements. We assume each observation is drawn from a mixture model for which each component represents one cause or disease class. The model addresses a major limitation of the traditional latent class approach by taking account of residual dependence among multivariate binary outcome ...
A Novel Method For Assessing Co-Monotonicity: An Interplay Between Mathematics And Statistics With Applications, 2015 The University of Western Ontario
A Novel Method For Assessing Co-Monotonicity: An Interplay Between Mathematics And Statistics With Applications, Danang T. Qoyyimi
Electronic Thesis and Dissertation Repository
Numerous problems in econometrics, insurance, reliability engineering, and statistics rely on the assumption that certain functions are monotonic, which may or may not be true in real life scenarios. To satisfy this requirement, from the theoretical point of view, researchers frequently model the underlying phenomena using parametric and semi-parametric families of functions, thus effectively specifying the required shapes of the functions. To tackle these problems in a non-parametric way, when the shape cannot be specified explicitly but only estimated approximately, we suggest indices for measuring the lack of monotonicity in functions. We investigate properties of these indices and offer convenient ...
Flexible Penalized Regression For Functional Data...And Other Complex Data Objects, 2015 New York University School of Medicine
Flexible Penalized Regression For Functional Data...And Other Complex Data Objects, Philip T. Reiss
Philip T. Reiss
No abstract provided.
Removing Inter-Subject Technical Variability In Magnetic Resonance Imaging Studies, 2015 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Removing Inter-Subject Technical Variability In Magnetic Resonance Imaging Studies, Jean-Philippe Fortin, Elizabeth M. Sweeney, John Muschelli, Ciprian M. Crainiceanu, Russell T. Shinohara, Alzheimer’S Disease Neuroimaging Initiative
UPenn Biostatistics Working Papers
Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008 ...
Sinkhole Vulnerability Mapping: Results From A Pilot Study In North Central Florida, 2015 Florida Geological Survey
Sinkhole Vulnerability Mapping: Results From A Pilot Study In North Central Florida, Clint Kromhout, Alan E. Baker
Sinkhole Conference 2015
At the end of June in 2012, Tropical Storm Debby dropped a record amount of rainfall across Florida which triggered hundreds, if not thousands, of sinkholes to form which resulted in tremendous damage to property. The Florida Division of Emergency Management contracted with the Florida Department of Environmental Protection’s Florida Geological Survey to produce a map depicting the state’s vulnerability to sinkhole formation. The three-year project began with a pilot study in three northern Florida counties: Columbia, Hamilton and Suwannee. Utilizing the statistical modeling method Weights of Evidence, results from the pilot study yielded a 93 percent success ...
Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, 2015 Bucknell University
Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, Mark J. Meyer, Jeffrey S. Morris, Craig P. Hersh, Jarrett D. Morrow, Christoph Lange, Brent A. Coull
Mark J Meyer
Current methods for conducting expression Quantitative Trait Loci (eQTL) analysis are limited in scope to a pairwise association testing between a single nucleotide polymorphism (SNPs) and expression probe set in a region around a gene of interest, thus ignoring the inherent between-SNP correlation. To determine association, p-values are then typically adjusted using Plug-in False Discovery Rate. As many SNPs are interrogated in the region and multiple probe-sets taken, the current approach requires the fitting of a large number of models. We propose to remedy this by introducing a flexible function-on-scalar regression that models the genome as a functional outcome. The ...
Code To Accompany Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, 2015 Bucknell University
Code To Accompany Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, Mark J. Meyer, Jeffrey S. Morris
Mark J Meyer
Code to accompany Ordinal probit wavelet-based functional models for eQTL analysis which is currently under review at Biostatistics. The code includes MATLAB files to run the OPWAVFM on a simulated sample dataset along with code to generate relevant graphics.
Functional Linear Models Extensions Uncover Pleiotropic Effects Of Chronic Pain Phenotypes, 2015 National Institute of Environmental Health Sciences
Functional Linear Models Extensions Uncover Pleiotropic Effects Of Chronic Pain Phenotypes, Dmitri V. Zaykin, L. Qing, G. D. Slade, R. Dubner, R. B. Fillingim, J. D. Greenspan, R. Ohrbach, W. Maixner, L. B. Diatchenko, Olga A. Vsevolozhskaya
Growing scientific evidence suggests that intricate interactions of genetic risk factors with environmental exposures play a major role in the development of chronic pain conditions. In studies of relative contribution of an individual’s genetic composition to the perception of pain, the general characteristics of pain sensitivity are typically measured by a wide range of different, yet possibly etiologically related pain phenotypes. Testing each of these pain-perception traits individually is subject to problems of multiple testing and low statistical power. Furthermore, pain-related traits may share common etiology and comprise binary, categorical, and quantitative measurements. In the current study, we propose ...
An Analysis Of The Characteristics And Practices Of Selected Alabama Small Livestock Producers: A Focus On Economics And Marketing, Jannette R. Bartlett, Nii O. Tackie, Mst Nusrat Jahan, Akua Adu-Gyamfi
Professional Agricultural Workers Journal
The study examined the characteristics and practices of small livestock producers, focusing on economics and marketing. Data were obtained from a convenience sample of 121 small producers from several South Central Alabama counties, and were analyzed using descriptive statistics, including chi-square tests. The socioeconomic characteristics reflected a higher proportion of part-time farmers; a higher proportion with at most a two-year/technical degree or some college education; and a higher proportion with $40,000 or less annual household income. A majority had been farming more than thirty years, and most had small herds. Also, very few made profits; many sold ...
Life As An Nfl Statistician, 2015 Miami Dolphins
Life As An Nfl Statistician, Dennis Lock
Mathematics Colloquium Series
Over the last few years, the fields of statistics and mathematics have become more prevalent and popular in professional sports (with the help of mainstream books and movies like Moneyball). The use of advanced (and non-advanced) statistical methods is growing across the sporting landscape from the front office to the media, and even into business and ticket sales. This talk will discuss Lock’s experiences building an analytics department with the Miami Dolphins as well as the general role of statistics in sports today. It will also including the recent analytics boom in the front office framework, the coinciding need ...
A Nonlinear Filter For Markov Chains And Its Effect On Diffusion Maps, 2015 Yale University
A Nonlinear Filter For Markov Chains And Its Effect On Diffusion Maps, Stefan Steinerberger
Yale Day of Data
Diffusion maps are a modern mathematical tool that helps to find structure in large data sets - we present a new filtering technique that is based on the assumption that errors in the data are intrinsically random to isolate and filter errors and thus boost the efficiency of diffusion maps. Applications include data sets from medicine (the Cleveland Heart Disease Data set and the Wisconsin Breast Cancer Data set) and engineering (the Ionosphere data set).
A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, 2015 Yale University
A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross
Yale Day of Data
Post-market surveillance is a collection of processes and activities used by product manufacturers and regulators, such as the U.S. Food and Drug Administration (FDA) to monitor the safety and effectiveness of medical devices once they are available for use “on the market”. These activities are designed to generate information to identify poorly performing devices and other safety problems, accurately characterize real-world device performance and clinical outcomes, and facilitate the development of new devices, or new uses for existing devices. Typically, a device is monitored by comparing adverse events in the exposed population to a matched unexposed population. This research ...