Statistics and Probability Commons^™

A Direct D-Bar Reconstruction Algorithm For Recovering A Complex Conductivity In 2d, Sarah J. Hamilton, C. N. L. Herrera, J. L. Mueller, A. Von Herrmann

Mathematics, Statistics and Computer Science Faculty Research and Publications

A direct reconstruction algorithm for complex conductivities in W^{2, ∞}(Ω), where Ω is a bounded, simply connected Lipschitz domain in R² , is presented. The framework is based on the uniqueness proof by Francini (2000 Inverse Problems 6 107–19), but equations relating the Dirichlet-to-Neumann to the scattering transform and the exponentially growing solutions are not present in that work, and are derived here. The algorithm constitutes the first D-bar method for the reconstruction of conductivities and permittivities in two dimensions. Reconstructions of numerically simulated chest phantoms with discontinuities at the organ boundaries are included.

Modeling Temporal Pattern And Event Detection Using Hidden Markov Model With Application To A Sludge Bulking Data, Naveen K. Bansal, Xin Feng, Wenjing Zhang, Wutao Wi, Yuanhao Zhao

Mathematics, Statistics and Computer Science Faculty Research and Publications

This paper discusses a method of modeling temporal pattern and event detection based on Hidden Markov Model (HMM) for a continuous time series data. We also provide methods for checking model adequacy and predicting future events. These methods are applied to a real example of sludge bulking data for detecting sludge bulking for a water plant in Chicago.

Characterizations Of Certain Continuous Univariate Distributions Based On The Conditional Distribution Of Generalized Order Statistics, M. Ahsanullah, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

The problem of characterizing probability distributions is an interesting problem which has recently attracted the attention of many researchers. Various characterization results have been established in different directions as reported in the literature. We present here, various characterizations of certain univariate continuous distributions based on the conditional distribution of generalized order statistics.

Secondary Structure Prediction Of Long Rna Sequences Based On Inversion Excursions And A Modularized Mapreduce Framework, Daniel Tesfai Yehdego

Open Access Theses & Dissertations

Ribonucleic acid (RNA) molecules and their secondary structures play important roles in many biological processes including gene expression and regulation. The genomes of many viruses are also RNA molecules. Since secondary structures are crucial for RNA functionality, computational predictions of the RNA secondary structures have been widely studied. However, the tremendous demands on computer memory and computing time for complex secondary structures limit the capability of existing thermodynamically based algorithms for structure predictions to handling only short RNA sequences with a few hundred bases. One approach to overcome this limitation is by first cutting long RNA sequences into shorter, non-overlapping …

Study Of Volatility Structures In Geophysics And Finance Using Garch Models, Francis Biney

Open Access Theses & Dissertations

This work investigates the underlying volatility processes in earthquake series, explosive series, high frequency (tick) data and financial indices. Furthermore it examines the applicability of a range of GARCH specifications for modeling volatility of these series in order to identify similarities and differences in the volatility structures. The GARCH

variants considered include the basic GARCH, IGARCH, ARFIMA (0,d,0)-GARCH and FIGARCH specifications. In all the applications the methodology provides insight into features of these series volatility.

Analysis Of Differential Item Functioning On Selected Items Assessing Conceptual Knowledge Of Descriptive Statistics For Spanish-Speaking Ell And Non-Ell College Students, Angelica Amy Monarrez Rodriguez

Open Access Theses & Dissertations

Recently, there has been growing interest in promoting conceptual understanding of statistical concepts in the classroom. The Assessment Resource Tools for Improving Statistical Thinking (ARTIST) project is a resource for maintaining and developing scales useful for measuring statistical conceptual knowledge. The focus of this study is to investigate whether items assessing conceptual knowledge of measures of center and variation from the (ARTIST) database show evidence of differential item functioning when administered to English Language Learners (ELLs). This is pertinent topic since the population of English Language Learners (ELL) in the United States has been growing rapidly in the past few …

The Dependent Samples T And Wilcoxon Sign Rank Maximum Test, Saverpierre Maggio

Wayne State University Dissertations

A maximum test using the parametric dependent samples t-test and the non-parametric Wilcoxon sign rank test was created using a FORTRAN program and various subroutines of the International Mathematical and Statistical Libraries (IMSL, 1980). Two tailed critical values were derived from a mixed normal distribution. Critical values obtained were at the 0.05, 0.025, 0.01 and 0.005 alpha levels via sample sizes (n) 8 through 30, 45, 60, 90 and 120. Critical values were compared to values obtained through the application of the Bonferroni correction method. It was concluded that the Bonferroni is an unnecessary method. Findings of the study are …

Linear Rank Tests Of Uniformity: Understanding Inconsistent Outcomes And The Construction Of New Tests, Anna E. Bargagliotti

Mathematics, Statistics and Data Science Faculty Works

Several nonparametric tests exist to test for differences among alternatives when using ranked data. Testing for differences among alternatives amounts to testing for uniformity over the set of possible permutations of the alternatives. Well-known tests of uniformity, such as the Friedman test or the Anderson test, are based on the impact of the usual limiting theorems (e.g. central limit theorem) and the results of different summary statistics (e.g. mean ranks, marginals, and pairwise ranks). Inconsistencies can occur among statistical tests' outcomes - different statistical tests can yield different outcomes when applied to the same ranked data. In this paper, we …

Using Etf Data To Monitor Systemic Risk, Melissa A. Siemer, Brett Amidan

STAR Program Research Presentations

In 2010, President Obama signed The Dodd-Frank Wall Street Reform and Consumer Protection Act, which requires financially based government agencies and 35 major US banks to monitor systemic risk. This was in response to the recent near financial collapse due to major mistakes made by organizations generally considered "too big to fail". Systemic risk is the risk of the collapse of an entire financial system or market. It refers to the risks imposed by interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a cascading failure. In April 2011, the …

Poverty And Disability: A Vicious Circle? Evidence From Afghanistan And Zambia, Jean-Francois Trani, Mitchell M. Loeb

Brown School Faculty Publications

Disability and poverty have a complex and interdependent relationship. It is commonly understood that persons with disabilities are more likely to be poor and that poverty may contribute to sustaining disability. This interdependency is revealed not only through an examination of poverty in terms of income but also on a broader scale through other poverty related dimensions. Just how robust is this link? This paper compares data collected from household surveys in Afghanistan and Zambia, and explores the potential link between multidimensional poverty and disability. We find evidence of lower access to health care, education and labour market for people …

Sieve Bootstrap Based Prediction Intervals And Unit Root Tests For Time Series, Maduka Rupasinghe

Doctoral Dissertations

"The application of the sieve bootstrap procedure, which resamples residuals obtained by fitting a finite autoregressvie (AR) approximation to empirical time series, to obtaining prediction intervals for integrated, long-memory, and seasonal time series as well as constructing a test for seasonal unit roots, is considered. The advantage of this resampling method is that it does not require knowledge about the underlying process generating a given time series and has been shown to work well for ARMA processes. We extend the application of the sieve bootstrap to ARIMA and FARIMA processes. The asymptotic properties of the sieve bootstrap prediction intervals for …

A Reply To David Richards’ Review Of Measuring Human Rights, Todd Landman, Edzia Carvalho

Human Rights & Human Welfare

Professor Richards highlights, in his generous review of our book Measuring Human Rights that one of the aims of the book is to bring to the forefront the importance of conceptualization before operationalization – that conceptual clarity (or lack of it) is at the heart of the problems concerning the measurement of human rights. He draws out three key issues from the book as the springboard for further discussion on measurement of the concept – a) the “Respect, Protect and Fulfill” (RPF) framework, b) the lack of reliable data sources, and c) the conceptual links between human rights, human development, …

Linear Mixed-Effects Models: Applications To The Behavioral Sciences And Adolescent Community Health, Lizmarie Gabriela Maldonado

USF Tampa Graduate Theses and Dissertations

Linear mixed-effects (LME) modeling is a widely used statistical method for analyzing repeated measures or longitudinal data. Such longitudinal studies typically aim to investigate and describe the trajectory of a desired outcome. Longitudinal data have the advantage over cross-sectional data by providing more accuracy for the model. LME models allow researchers to account for random variation among individuals and between individuals.

In this project, adolescent health was chosen as a topic of research due to the many changes that occur during this crucial time period as a precursor to overall well-being in adult life. Understanding the factors that influence how …

Spatially Dense Drip Hydrological Monitoring And Infiltration Behaviour At The Wellington Caves, South East Australia, Catherine N. Jex, Gregoire Mariethoz, Andy Baker, Peter Graham, Martin S. Andersen, Ian Acworth, Nerilee Edwards, Cecilia Azcurra

International Journal of Speleology

Despite the fact that karst regions are recognised as significant groundwater resources, the nature of groundwater flow paths in the unsaturated zone of such fractured rock is at present poorly understood. Many traditional methods for constraining groundwater flow regimes in karst aquifers are focussed on the faster drainage components and are unable to inform on the smaller fracture or matrix-flow components of the system. Caves however, offer a natural inception point to observe both the long term storage and the preferential movement of water through the unsaturated zone of such fractured carbonate rock by monitoring of drip rates of stalactites, …

Statistical Content In Middle Grades Mathematics Textbooks, Maria Consuelo (Suzie) Capiral Pickle

USF Tampa Graduate Theses and Dissertations

Statistical Content in Middle Grades Mathematics Textbooks

Maria Consuelo (Suzie) Capiral Pickle

Abstract

This study analyzed the treatment and scope of

statistical concepts in four, widely-used, contemporary, middle

grades mathematics textbook series: Glencoe Math Connects,

Prentice Hall Mathematics, Connected Mathematics Project, and

University of Chicago School Mathematics Project. There were

three phases for the data analysis. Phase 1 addressed the location

and sequence of the statistical concepts. Phase 2 focused upon an

examination of the lesson narrative, its components and scope.

Phase 3 analyzed the level of cognitive demand required of the

students to complete the exercises, and the total …

Statistical Estimation Of Physiologically-Based Pharmacokinetic Models: Identifiability, Variation, And Uncertainty With An Illustration Of Chronic Exposure To Dioxin And Dioxin-Like-Compounds., Zachary John Thompson

USF Tampa Graduate Theses and Dissertations

Assessment of human exposure to environmental chemicals is inherently subject to uncertainty and variability. There are data gaps concerning the inventory, source, duration, and intensity of exposure

as well as knowledge gaps regarding pharmacokinetics in general. These gaps result in uncertainties in exposure assessment.

The uncertainties compound further with variabilities due to population variations regarding stage of life, life style, and susceptibility,

etc. Use of physiologically-based pharmacokinetic (PBPK) models promises to reduce the uncertainties and enhance extrapolation between species, between routes, from high to low dose, and from acute to chronic exposure. However, fitting PBPK models is challenging because of …

Stochastic Modeling Of Network-Centric Epidemiological Processes, Divine Wanduku

USF Tampa Graduate Theses and Dissertations

The technological changes and educational expansion have created the heterogeneity in the human species. Clearly, this heterogeneity generates a structure in the population

dynamics, namely: citizen, permanent resident, visitor, and etc. Furthermore, as the heterogeneity in the population increases, the human mobility between meta-populations patches

also increases. Depending on spatial scales, a meta-population patch can be decomposed into sub-patches, for examples: homes, neighborhoods, towns, etc. The dynamics of human

mobility in a heterogeneous and scaled structured population is still its infancy level. We develop and investigate (1) an algorithmic two scale human mobility dynamic model for a meta-population. Moreover,the two …

Evaluation Of Repeated Biomarkers: Non-Parametric Comparison Of Areas Under The Receiver Operating Curve Between Correlated Groups Using An Optimal Weighting Scheme, Ping Xu

USF Tampa Graduate Theses and Dissertations

Receiver Operating Characteristic (ROC) curves are often used to evaluate the prognostic performance of a continuous biomarker. In a previous research, a non-parametric ROC approach was introduced to compare two biomarkers with repeated measurements. An asymptotically normal statistic, which contains the subject-specific weights, was developed to estimate the areas under the ROC curve of biomarkers. Although two weighting schemes were suggested to be optimal when the within subject correlation is 1 or 0 by the previous study, the universal optimal weight was not determined. We modify this asymptotical statistic to compare AUCs between two correlated groups and propose a solution …

Bayesian Inference On Mixed-Effects Models With Skewed Distributions For Hiv Longitudinal Data, Ren Chen

USF Tampa Graduate Theses and Dissertations

Statistical models have greatly improved our understanding of the pathogenesis of HIV-1 infection

and guided for the treatment of AIDS patients and evaluation of antiretroviral (ARV) therapies.

Although various statistical modeling and analysis methods have been applied for estimating the

parameters of HIV dynamics via mixed-effects models, a common assumption of distribution is

normal for random errors and random-effects. This assumption may lack the robustness against

departures from normality so may lead misleading or biased inference. Moreover, some covariates

such as CD4 cell count may be often measured with substantial errors. Bivariate clustered

(correlated) data are also commonly encountered in …

Statistical Modeling And Analysis Of Breast Cancer And Pancreatic Cancer, Zahra Kottabi

USF Tampa Graduate Theses and Dissertations

Abstract

The object of the present study is to apply statistical modeling and estimate the mean of optimism of breast cancer patients as function of attribute variables; delay, education and age for each race of breast cancer patients. Moreover, to investigate the nonlinear association between optimism, education, age and delay with respect to each race and both. Furthermore, to develop differential equations that will characterize the behavior of the pancreatic cancer tumor size as a function of time. Having such differential equations, the mean solution of which once plotted will identify the rate of change of tumor size as a …