Multivariate Analysis Commons^™

Flexible Partially Linear Single Index Regression Models For Multivariate Survival Data, Na Lei

Electronic Thesis and Dissertation Repository

Survival regression models usually assume that covariate effects have a linear form. In many circumstances, however, the assumption of linearity may be violated. The present work addresses this limitation by adding nonlinear covariate effects to survival models. Nonlinear covariates are handled using a single index structure, which allows high-dimensional nonlinear effects to be reduced to a scalar term. The nonlinear single index approach is applied to modeling of survival data with multivariate responses, in three popular models: the proportional hazards (PH) model, the proportional odds (PO) model, and the generalized transformation model. Another extension of the PH and PO model …

Reaching The Gold Standard: Assessing Driving Ability Among Student And Expert Drivers, Alyssa Davis

Statistics

No abstract provided.

Joint Estimation Of Multiple Graphical Models From High Dimensional Time Series, Huitong Qiu, Fang Han, Han Liu, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript the problem of jointly estimating multiple graphical models in high dimensions is considered. It is assumed that the data are collected from n subjects, each of which consists of m non-independent observations. The graphical models of subjects vary, but are assumed to change smoothly corresponding to a measure of the closeness between subjects. A kernel based method for jointly estimating all graphical models is proposed. Theoretically, under a double asymptotic framework, where both (m,n) and the dimension d can increase, the explicit rate of convergence in parameter estimation is provided, thus characterizing the strength one can borrow …

A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria Del Pilar Orjuela

FIU Electronic Theses and Dissertations

Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population.

This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and …

Sparse Median Graphs Estimation In A High Dimensional Semiparametric Model, Fang Han, Han Liu, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph, which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upper bound on the rate of convergence is given. Experiments on both …

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

Perceived Attitudes And Staff Roles Of Community Based Outpatient Clinics In Disaster Management, Pauline Antoinette Hodge-Hilton

Loma Linda University Electronic Theses, Dissertations & Projects

Objective: Natural and manmade disasters have claimed the lives of thousands of individuals in the US and caused billions of dollars in property damage. First responders carry the responsibility of disaster management, leaving other health care professionals such as medical clinic staff underutilized to support the clinic staff. We explored how medical and support staff in Community-based Outpatient VHA Clinics (CBOC) perceive their roles in disaster response, their attitudes about clinic readiness and continuity of care during disasters, and their ability to function in a post disaster environment.

Methods: A mixed method study was conducted to answer questions related to …

Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel

Ole J Mengshoel

Exploring Multiple Dimensions Of Parallelism In Junction Tree Message Passing, Lu Zheng, Ole J. Mengshoel

Ole J Mengshoel

Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh

Ole J Mengshoel

Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara

Ole J Mengshoel

Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche

Ole J Mengshoel

Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards

Doctoral Dissertations

Many key decisions and design policies are made using sophisticated computer simulations. However, these sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. This dissertation's goal is to address these simulation deficiencies by presenting a general automated process for tuning simulation inputs such that simulation output matches real world measured data. The automated process involves the following key components -- 1) Identify a model that accurately estimates the real world simulation calibration target from measured sensor data; 2) Identify …

Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong

Dissertations & Theses (Open Access)

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays …

A Bayesian Regression Tree Approach To Identify The Effect Of Nanoparticles Properties On Toxicity Profiles, Cecile Low-Kam, Haiyuan Zhang, Zhaoxia Ji, Tian Xia, Jeffrey I. Zinc, Andre Nel, Donatello Telesca

COBRA Preprint Series

We introduce a Bayesian multiple regression tree model to characterize relationships between physico-chemical properties of nanoparticles and their in-vitro toxicity over multiple doses and times of exposure. Unlike conventional models that rely on data summaries, our model solves the low sample size issue and avoids arbitrary loss of information by combining all measurements from a general exposure experiment across doses, times of exposure, and replicates. The proposed technique integrates Bayesian trees for modeling threshold effects and interactions, and penalized B-splines for dose and time-response surfaces smoothing. The resulting posterior distribution is sampled via a Markov Chain Monte Carlo algorithm. This …

“Seeing” The Elephant: Assessing The Impact Of Library-Composition Program Collaboration On First-Year Student Learning, Erin E. Rinto

Library Faculty Presentations

Though university libraries and composition programs have historically collaborative relationships, these partnerships can take a variety of formats, including single course period library sessions, teaching-the-teachers, and librarian-driven assignment models. A hybrid of these collaborative approaches was implemented Fall 2012 at UNLV in an effort to provide first-year composition students with a more systematic information literacy experience in the required ENG 102 course. A two-pronged assessment method was used to evaluate the impact of the collaboration for both first-year student learning as well as to implement programmatic change.

Global Quantitative Assessment Of The Colorectal Polyp Burden In Familial Adenomatous Polyposis Using A Web-Based Tool, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi

Jeffrey S. Morris

Background: Accurate measures of the total polyp burden in familial adenomatous polyposis (FAP) are lacking. Current assessment tools include polyp quantitation in limited-field photographs and qualitative total colorectal polyp burden by video.

Objective: To develop global quantitative tools of the FAP colorectal adenoma burden.

Design: A single-arm, phase II trial.

Patients: Twenty-seven patients with FAP.

Intervention: Treatment with celecoxib for 6 months, with before-treatment and after-treatment videos posted to an intranet with an interactive site for scoring.

Main Outcome Measurements: Global adenoma counts and sizes (grouped into categories: less than 2 mm, 2-4 mm, and greater than 4 mm) were …

Epistemology And Synthesis: Instrumental Neutron Activation Analysis And The Caddo Tradition, Robert Z. Selden Jr.

CRHR: Archaeology

The statistical groupings illustrated herein represent the current iteration of Caddo INAA compositional groups based upon the chemical composition of archaeologically-recovered ceramics. For some time, a number of Caddo archaeologists have thought these results to be lacking. This poster symbolizes the first step toward a new interpretation of chemical composition groups, and the initial instancce within which GIS has been employed as an analytical tool.

Consilience: Radiocarbon, Instrumental Neutron Activation Analysis, And Litigation In The Ancestral Caddo Region, Robert Z. Selden Jr.

CRHR: Archaeology

Through the creation and analysis of databases for radiocarbon, instrumental neutron activation analysis (INAA), and law, macro-level trends are exposed that form the framework of a broader research program aimed at advancing ideas of craft specialization and archaeological theory in the ancestral Caddo region of Southwest Arkansas, Northwest Louisiana, Northeast Texas, and Southeast Oklahoma. The findings of this investigation illustrate the research potential that remains buried within the context of cultural resource management (CRM) reports and legal databases (Westlaw and LexisNexis) that is awaiting consumption within regional research designs aimed at exploring the nuances and trends that appear through synthetic …

Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

The SAS macro was developed to calculate the kappa statistic for the clustered matched-pair data.

James-Stein Type Compound Estimation Of Multiple Mean Response Functions And Their Derivatives, Limin Feng

Theses and Dissertations--Statistics

Charnigo and Srinivasan originally developed compound estimators to nonparametrically estimate mean response functions and their derivatives simultaneously when there is one response variable and one covariate. The compound estimator maintains self consistency and almost optimal convergence rate. This dissertation studies, in part, compound estimation with multiple responses and/or covariates. An empirical comparison of compound estimation, local regression and spline smoothing is included, and near optimal convergence rates are established in the presence of multiple covariates.

James and Stein proposed an estimator of the mean vector of a p dimensional multivariate normal distribution, which produces a smaller risk than the maximum …

Multiscale Analysis Of Factors That Affect The Distribution Of Sharks Throughout The Northern Gulf Of Mexico, J. Marcus Drymon, Laure Carassou, Sean P. Powers, Mark Grace, John Dindo, Brian Dzwonkowski

University Faculty and Staff Publications

Identification of the spatial scale at which marine communities are organized is critical to proper management, yet this is particularly difficult to determine for highly migratory species like sharks. We used shark catch data collected during 2006–09 from fishery- independent bottom-longline surveys, as well as biotic and abiotic explanatory data to identify the factors that affect the distribution of coastal sharks at 2 spatial scales in the northern Gulf of Mexico. Centered principal component analyses (PCAs) were used to visualize the patterns that characterize shark distributions at small (Alabama and Mississippi coast) and large (northern Gulf of Mexico) spatial scales. …

Mapping And Decomposing Scale-Dependent Soil Moisture Variability Within An Inner Bluegrass Landscape, Carla Landrum

Theses and Dissertations--Plant and Soil Sciences

There is a shared desire among public and private sectors to make more reliable predictions, accurate mapping, and appropriate scaling of soil moisture and associated parameters across landscapes. A discrepancy often exists between the scale at which soil hydrologic properties are measured and the scale at which they are modeled for management purposes. Moreover, little is known about the relative importance of hydrologic modeling parameters as soil moisture fluctuates with time. More research is needed to establish which observation scales in space and time are optimal for managing soil moisture variation over large spatial extents and how these scales are …

A Comparison Of Periodic Autoregressive And Dynamic Factor Models In Intraday Energy Demand Forecasting, Thomas Mestekemper, Goeran Kauermann, Michael Smith

Michael Stanley Smith

We suggest a new approach for forecasting energy demand at an intraday resolution. Demand in each intraday period is modeled using semiparametric regression smoothing to account for calendar and weather components. Residual serial dependence is captured by one of two multivariate stationary time series models, with dimension equal to the number of intraday periods. These are a periodic autoregression and a dynamic factor model. We show the benefits of our approach in the forecasting of district heating demand in a steam network in Germany and aggregate electricity demand in the state of Victoria, Australia. In both studies, accounting for weather …

Bayesian Approaches To Copula Modelling, Michael S. Smith

Michael Stanley Smith

Copula models have become one of the most widely used tools in the applied modelling of multivariate data. Similarly, Bayesian methods are increasingly used to obtain efficient likelihood-based inference. However, to date, there has been only limited use of Bayesian approaches in the formulation and estimation of copula models. This article aims to address this shortcoming in two ways. First, to introduce copula models and aspects of copula theory that are especially relevant for a Bayesian analysis. Second, to outline Bayesian approaches to formulating and estimating copula models, and their advantages over alternative methods. Copulas covered include Archimedean, copulas constructed …