Physical Sciences and Mathematics Commons^™

Statistical Partition Problem For Exponential Populations And Statistical Surveillance Of Cancers In Louisiana, Jin Gu

University of New Orleans Theses and Dissertations

In this dissertation, we consider the problem of partitioning a set of

k population with respect

to a control population. For this problem some multistage methodologies are proposed and their

properties are derived. Using the Monte Carlo simulation techniques, the small and moderate

sample size performance of the proposed procedure are studied.

We have also considered at statistical surveillance of various cancers in Louisiana.

Methods For Identifying Regions Of Brain Activation Using Fmri Meta-Data, Meredith A. Ray

Theses and Dissertations

Functional neuroimaging is a relatively young discipline within the neurosciences that has led to significant advances in our understanding of the human brain and progress in neuroscientific research related to public health. Accurately identifying activated regions in the brain showing a strong association with an outcome of interest is crucial in terms of disease prediction and prevention. Functional magnetic resonance imaging (fMRI) is the most widely used method for this type of study as it has the ability to measure and identify the location of changes in tissue perfusion, blood oxygenation, and blood volume. In practice, the three-dimensional brain locations …

Simulation Based Evaluation Of Multiscale Small Area Health Models, Purbasha Dasgupta

Theses and Dissertations

The effects of scale on the analysis of spatial data, often referred to as the modifiable areal unit problem in spatial studies, is one of the issues often encountered in small area health models. These spatial effects of scale are also seen in the areas of disease mapping where data are usually available in counts. Often there is a need to consider the different scales of aggregation that exist within count data, since inferences based on analyses can vary if we change the definition of the unit of analysis. This thesis provides a framework that describes the distribution of relative …

Semiparametric Regression Analysis Of Bivariate Interval-Censored Data, Naichen Wang

Theses and Dissertations

Survival analysis is a long-lasting and popular research area and has numerous applications in all fields such as social science, engineering, economics, industry, and public health. Interval-censored data are a special type of survival data, in which the survival time of interest is never exactly observed but is known to fall within some observed interval. Interval-censored data arise commonly in real-life studies, in which subjects are examined at periodical or irregular follow-up visits. In this dissertation, we develop efficient statistical approaches for regression analysis of bivariate intervalcensored data, in which the two survival times of interest are correlated and both …

Viewing The Moon In Infrared, Kyle Beekman

Statistics

Man has been fascinated by the heavens since ancient times, yet there is still so much that we don’t know. This project was created by Dr. Gary Hughes with goal of obtaining information about the moon and other objects in the vicinity of the Earth. The project was mostly experimental in nature and there was no specific goal at the outset of the project. In the end the project focused on the moon and meteors that traveled through the Earth’s upper atmosphere. Throughout the month of August, students traveled to the Mount Barcroft Research Station in the Eastern Sierras to …

Analyzing Alcohol Behavior In San Luis Obispo, Ariana Montes

Statistics

No abstract provided.

A Markov Model For Baseball With Applications, Daniel Joseph Ursin

Theses and Dissertations

In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data. We describe the transition matrices for individual player data and their use in generating single and nine-inning run distributions for a given lineup. The run distribution is used to calculate the expected number of runs produced by a lineup over nine innings. We discuss batting order optimization heuristics to avoid computation of distributions for the 9! = 362, 880 distinct lineups for 9 players. Finally, we describe an implementation of the algorithms and review their performance against actual game data.

Reliability-Based Design And Acceptance Protocol For Driven Piles, Joseph Jabo

Graduate Theses and Dissertations

The current use of the Arkansas Standard Specifications for Highway Construction Manuals (2003, 2014) for driven pile foundations faces various limitations which result in designs of questionable reliability. These specifications are based on the Allowable Stress Design method (ASD), cover a wide range of uncertainties, do not take into account pile and soil types, and were developed for general use. To overcome these challenges it is deemed necessary to develop a new design and acceptance protocol for driven piles. This new protocol incorporates locally calibrated RLFD resistance factors for accounting for local design and construction experiences and practices, as well …

Lnference On Differences In K Means For Data With Excess Zeros And Detection Limits, Haolai Jiang

Dissertations

Many data have excess zeros or unobservable values falling below detection limit. For example, data on hospitalization costs incurred by members of a health insurance plan will have zeros for the percentage who did not get sick. Benzene exposure measurements on petroleum re nery workers have some exposures fall below the limit of detection. Traditional methods of inference like one-way ANOVA are not appropriate to analyze such data since the point mass at zero violates typical distribution assumptions.

For testing for equality of means of k distributions, we will propose a likelihood ratio test that accounts for excess zeros or …

Online Detection Of Outliers And Structural Breaks Using Sequential Monte Carlo Methods, Richard Wanjohi

Graduate Theses and Dissertations

Outliers and structural breaks occur quite frequently in time series data. Whereas outliers often contain valuable information

about the process under study, they are known to have serious negative impact on statistical data analysis. Most obvious effect is model misspecification and biased parameter estimation which results in wrong conclusions and inaccurate predictions. Structural time series consist of underlying features such as level, slope, cycles or seasonal components. Structural breaks are permanent disruptions of one or more of these components and might be a signal of serious changes in the observed process.

Detecting outliers and estimating the location of structural breaks …

Inferential Procedures For Dominance Analysis Measures In Multiple Regression, Shuwen Tang

Theses and Dissertations

In order to better interpret a selected multiple regression model, researchers are often interested in whether a predictor is significantly more important than another or not. This study investigates the performance of the Normal-Theory based (asymptotic) confidence interval and bootstrap confidence intervals for predictors' dominance relationships using both normal and non-normal data. The results show that asymptotic confidence interval method is adequate to make inferences for comparing two general dominance measures when the distribution is multivariate normal or slightly non-normal and when the effect size is no less than 0.15 and the sample size is at least 100. However, the …

A Vegetation Analysis On Horn Island, Mississippi, Ca. 1940 Using Characteristic Dimensions Derived From Historical Aerial Photography, Guy Wilburn Jeter Jr.

Master's Theses

Horn Island is part of the MS/AL barrier island chain in the northern Gulf of Mexico located approximately 18kn off the coast of Mississippi. This island’s habitats have undergone many transitions over the last several decades. The goal of this study was to quantify habitat change over a seventy year period using historical black and white photography from 1940. Using present NAIP imagery from the USDA, habitat structure was estimated by using geo-statistics, and second order statistics, from a co-occurrence matrix, to characterize texture for habitat classification. Percent land cover was then calculated to determine overall land cover change over …

Security Analysis On Network Systems Based On Some Stochastic Models, Xiaohu Li

University of New Orleans Theses and Dissertations

Due to great effort from mathematicians, physicists and computer scientists, network science has attained rapid development during the past decades. However, because of the complexity, most researches in this area are conducted only based upon experiments and simulations, it is critical to do research based on theoretical results so as to gain more insight on how the structure of a network affects the security. This dissertation introduces some stochastic and statistical models on certain networks and uses a k-out-of-n tolerant structure to characterize both logically and physically the behavior of nodes. Based upon these models, we draw several illuminating results …

The Phenomenon Of Outbound Medical Tourism In The United States, Tanner Douglas Cabbage

Chancellor’s Honors Program Projects

No abstract provided.

Assessing The Social And Ecological Factors That Influence Childhood Overweight And Obesity, Katie Callahan

Electronic Theses and Dissertations

The prevalence of childhood overweight and obesity is increasing at an alarming rate in the United States. Currently more than 1 in 3 children aged 2-19 are overweight or obese. This is of major concern because childhood overweight and obesity leads to chronic conditions such as type II diabetes and tracks into adulthood, where more severe adverse health outcomes arise. In this study I used the premise of the social ecological model (SEM) to analyze the common levels that a child is exposed to daily; the intrapersonal level, the interpersonal level, the school level, and the community level to better …

Computational Communication Intelligence: Exploring Linguistic Manifestation And Social Dynamics In Online Communication, Xiaoxi Xu

Doctoral Dissertations

We now live in an age of online communication. As social media becomes an integral part of our life, online communication becomes an essential life skill. In this dissertation, we aim to understand how people effectively communicate online. We research components of success in online communication and present scientific methods to study the skill of effective communication. This research advances the state of art in machine learning and communication studies. For communication studies, we pioneer the study of a communication phenomenon we call Communication Intelligence in online interactions. We create a theory about communication intelligence that measures participants’ ten high-order …

Data Analysis And Study Design In The Presence Of Error-Prone Diagnostic Tests, Xiangdong Gu

Doctoral Dissertations

Interval censored time to event outcomes arise when a silent event of interest is known to have occurred within a specific time period, determined by the times of the last negative and first positive diagnostic tests. The four chapters comprising this thesis are tied together by a common theme in that the outcome of interest is an interval censored time to event random variable. In Chapter 1, we describe a stratified Weibull model appropriate for interval cen- sored outcomes and implement a new R package straweib. We compare the proposed approach with the log-linear form of the Weibull regression model …

Estimating Prevalence From Complex Surveys, Sophie O'Brien

Masters Theses

Massachusetts passed legislation in the fall of 2012 to allow the construction of three casinos and a slot parlor in the state. The prevalence of problem gambling in the state and in areas where casinos will be constructed is of particular interest. The goal is to evaluate the change in prevalence after construction of the casinos, using a multi-mode address based sample survey. The objective of this thesis is to evaluate and describe ways of using statistical inference to estimates prevalence rates in finite populations. Four methods were considered in an attempt to evaluate the prevalence of problem gambling in …

Censored Time Series Analysis, Nagham Muslim Mohammad

Electronic Thesis and Dissertation Repository

Environmental data is frequently left or right censored. This is due to the fact that the correct value for observed values that are below or above some threshold or detection point are inaccurate so that it is only known for sure that the true value is below or above that threshold. This is frequently important with water quality and air quality time series data. Interval censoring occurs when the correct values of the data are known only for those values falling above some lower threshold and below some upper threshold. Censoring threshold values may change over time, so multiple censor …

Probabilistic Uncertainty Quantification And Experiment Design For Nonlinear Models: Applications In Systems Biology, Vu Cao Duy Thien Dinh

Open Access Dissertations

Despite the ever-increasing interest in understanding biology at the system level, there are several factors that hinder studies and analyses of biological systems. First, unlike systems from other applied fields whose parameters can be effectively identified, biological systems are usually unidentifiable, even in the ideal case when all possible system outputs are known with high accuracy. Second, the presence of multivariate bifurcations often leads the system to behaviors that are completely different in nature. In such cases, system outputs (as function of parameters/inputs) are usually discontinuous or have sharp transitions across domains with different behaviors. Finally, models from systems biology …

Application Of Bayesian Networks In Consumer Service Industry, Yuan Gao

Open Access Theses

Gao, Yuan. M.S.I.E., Purdue University. December 2014. Application of Bayesian Networks in Consumer Service Industry. Major professor: Vincent G. Duffy The purpose of the present study is to explore the application of Bayesian networks in the consumer service industry to model causal relationships within complex risk factor structures using aggregate data. An analysis of the Hawaii tourism market was conducted to find out how visitor characteristics affect their behavior and experience as consumers during the trips, and influence the tourism market outcomes represented by measurable factors. Two hypotheses were proposed regarding the use of aggregate data and the influence of …

On The Occurrences Of Motifs In Recursive Trees, With Applications To Random Structures, Mohan Gopaladesikan

Open Access Dissertations

In this dissertation we study three problems related to motifs and recursive trees. In the first problem we consider a collection of uncorrelated motifs and their occurrences on the fringe of random recursive trees. We compute the exact mean and variance of the multivariate random vector of the counts of occurrences of the motifs. We further use the Cramér-Wold device and the contraction method to show an asymptotic convergence in distribution to a multivariate normal random variable with this mean and variance. ^ The second problem we study is that of the probability that a collection of motifs (of the …

Divide And Recombine: Autoregressive Models And Stl+, Xiang Han

Open Access Dissertations

In this thesis multiple methods are proposed and applied to the Akamai CIDR time series data. The Akamai network is one of the world's largest distributed-computing platforms, with more than 250,000 servers in more than 80 countries. It is responsible for 15-20 percent of all web traffic. We obtained 110 GB raw CIDR data over a 18 month period, collected on the Akamai network from November 2011 to April 2013. ^ The Seasonal-Trend Decomposition procedure based on loess (STL+) is used to model the CIDR series. Motivated by the CIDR series analysis, we propose a general prediction based model selection …

Spatial Marked Point Processes: Models And Inferences, Yen-Ning E Huang

Open Access Dissertations

A spatial marked point process describes the locations of randomly distributed events in a region, with a mark attached to each observed point. Nowadays, the availability of spatiotemporal data is increasing and many spatiotemporal models are studied with applications in a wide range of disciplines. Spatial marked point processes are then extended to spatiotemporal marked point processes if time component is taken into account. In general, the marks can be quantitative or categorical variables. Independence between points and marks is a convenient assumption, but may not be true in practice. Tests for independence between points and marks are proposed previously, …

The Tessera D&R Computational Environment: Designed Experiments For R-Hadoop Performance And Bitcoin Analysis, Jianfu Li

Open Access Dissertations

D&R is a statistical framework for the analysis of large complex data that enables feasible and practical analysis of large complex data. The analyst selects a division method to divide the data into subsets, applies an analytic method of the analysis to each subset independently with no communication among subsets, selects a recombination method that is applied to the outputs across subsets to form a result of the analytic method for the entire data. The computational tasking of D&R is nearly embarrassingly parallel, so D&R can readily exploit distributed, parallel computational environments, such as our D&R computational environment, Tessera.^ In …

Scaling Mcmc Inference And Belief Propagation To Large, Dense Graphical Models, Sameer Singh

Doctoral Dissertations

With the physical constraints of semiconductor-based electronics becoming increasingly limiting in the past decade, single-core CPUs have given way to multi-core and distributed computing platforms. At the same time, access to large data collections is progressively becoming commonplace due to the lowering cost of storage and bandwidth. Traditional machine learning paradigms that have been designed to operate sequentially on single processor architectures seem destined to become obsolete in this world of multi-core, multi-node systems and massive data sets. Inference for graphical models is one such example for which most existing algorithms are sequential in nature and are difficult to scale …

Evaluating Predictors Of An Individual’S Dietary Intake Latent Value Under Different Mixed Models, Shuli Yu

Doctoral Dissertations

The accurate estimation of an individual’s usual dietary intake is important since the estimates are essential to uncover the diet-disease relationships. This study explores a more accurate method to estimate an individual’s latent value of usual dietary intake when it is repeatedly measured using a 24-hour dietary recall (24HR) and seven day dietary recall (7DDR), accounting for random measurement error and bias. The performance of the (empirical) predictor of subject’s latent value obtained under the finite population mixed model (FPMM) framework is compared with those obtained under the usual mixed model and the measurement error model through a simulation study. …

Incorporating Boltzmann Machine Priors For Semantic Labeling In Images And Videos, Andrew Kae

Doctoral Dissertations

Semantic labeling is the task of assigning category labels to regions in an image. For example, a scene may consist of regions corresponding to categories such as sky, water, and ground, or parts of a face such as eyes, nose, and mouth. Semantic labeling is an important mid-level vision task for grouping and organizing image regions into coherent parts. Labeling these regions allows us to better understand the scene itself as well as properties of the objects in the scene, such as their parts, location, and interaction within the scene. Typical approaches for this task include the conditional random field …

The Selecting And Risk Analysis Of Temporary Anchor Positions In The Port Area Of Qinhuangdao, Shangying Zhang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Analysis Of Energy-Based Carbon Emission From Landside Operations Of Container Terminal And Its Abatement Strategies, Dwi Astuti

World Maritime University Dissertations

No abstract provided.