Statistics and Probability Commons^™

Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert

Branch Mathematics and Statistics Faculty and Staff Publications

This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.

Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh

Branch Mathematics and Statistics Faculty and Staff Publications

This article addresses the problem of estimating the population mean using auxiliary information in the presence of measurement errors.

Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our …

Detecting Temporal Patterns Using Reconstructed Phase Space And Support Vector Machine In The Dynamic Data System, Wenjing Zhang, Xin Feng

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this paper we present a method for detecting dynamic temporal patterns that are characteristic and predictive of significant events in a dynamic data system. We employ the Gaussian Mixture Model (GMM) to cluster the data sequence into three categories of signals, e.g. normal, patterns and events. The data sequence is then embedded into a Reconstructed Phase Space (RPS) which is topologically equivalent to the dynamics of the original system. We apply a hybrid method using Support Vector Machines (SVM) and Maximum a Posterior (MAP) to classify temporal pattern signals based on the event function. We performed two experimental applications …

On The First-Order Expressibility Of Lattice Properties To Unicoherence In Continua, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

Many properties of compacta have “textbook” definitions which are phrased in lattice-theoretic terms that, ostensibly, apply only to the full closed-set lattice of a space. We provide a simple criterion for identifying such definitions that may be paraphrased in terms that apply to all lattice bases of the space, thereby making model-theoretic tools available to study the defined properties. In this note we are primarily interested in properties of continua related to unicoherence; i.e., properties that speak to the existence of “holes” in a continuum and in certain of its subcontinua.

Impact Of Curriculum Reform: Evidence Of Change In Classroom Instruction In The United States, John Moyer, Jinfa Cai, Ning Wang, Bikai Nie

Mathematics, Statistics and Computer Science Faculty Research and Publications

The purpose of the study reported in this article is to examine the impact of curriculum on instruction. Over a three-year period, we observed 579 algebra-related lessons in grades 6–8. Approximately half the lessons were taught in schools that had adopted a Standards-based mathematics curriculum called the Connected Mathematics Program (CMP), and the remainder of the lessons were taught in schools that used more traditional curricula (non-CMP). We found many significant differences between the CMP and non-CMP lessons. The CMP lessons, emphasized the conceptual aspects of instruction to a greater extent than the non-CMP lessons and the non-CMP lessons …

A Characterization Of Connected (1,2)-Domination Graphs Of Tournaments, Kim A. S. Factor, Larry J. Langley

Mathematics, Statistics and Computer Science Faculty Research and Publications

Recently. Hedetniemi et aI. introduced (1,2)-domination in graphs, and the authors extended that concept to (1, 2)-domination graphs of digraphs. Given vertices x and y in a digraph D, x and y form a (1,2)-dominating pair if and only if for every other vertex z in D, z is one step away from x or y and at most two steps away from the other. The (1,2)-dominating graph of D, dom_1,2 (D), is defined to be the graph G = (V, E ) , where V (G) = V (D), and xy is …

On The Distributions Of Certain Spacings, Gholamhossein Hamedani, Hans Volkmer

Mathematics, Statistics and Computer Science Faculty Research and Publications

A characterization of the uniform distribution based on distributions of spacings is presented which extends the existing result in this direction. Also, a result on the distribution of spacings for distributions close to the uniform one is discussed.

Bayesian Computational Methods For Hidden Markov Models, Samson Laine Ghebremariam

Open Access Theses & Dissertations

Hidden Markov Models (HMMs) have been applied to many real-world problems. Hidden Markov modeling has recently become increasingly important and popular among researchers,and many software tools are based on them. Given that the models are rich in mathematical structure, they can form theoretical foundation for use in a wide range of applications. Hidden Markov models provide a universal configuration for statistical analysis of a large variety of DNA sequences containing symbols A, C, G, T. In a HMM, it is impossible to figure out what state the model is in by just having a look at the symbol generated.

A …

A Proposed Epithermal Model For The High Grade District, California, Michael Nicholas Feinstein

Open Access Theses & Dissertations

A historic gold mining district in northeastern California has not been incorporated into the global knowledge base for precious metal vein deposits. This study collected various data types which are important characteristics in the classification and understanding of vein deposits. The High Grade District (HGD) is a gold mining site located in the northeast corner of Modoc County, California, in the Warner Mountains. The Warner Mountains are composed of Tertiary eruptive centers, cropping out between valleys formed through extensional tectonics. Mineralization of the HGD displays abundant silicification, adularia, and gold; these characteristics are sufficient to classify mineralization as low-sulfidation epithermal …

Gamma And Generalized Gamma Distributions, Victor Hugo Jiménez Nava

Open Access Theses & Dissertations

We present the Generalized Gamma Distribution, study its properties and derive the estimators of the parameters. This distribution includes many standard forms, like: Gamma, Exponential, Weibull, Half Normal and others. Sum and ratios of independent generalized gamma lead to intractable forms. However approximation works well. In particular two-moment gamma and three moment normal approximations are shown to approximate the sum of k independent gamma as well as generalized gamma distributions.

Principal Differential Analysis With Covariates : A Simulation Study On The Effect Of The Smoothing Parameters, Indika Varuna Mallawaarachchi

Open Access Theses & Dissertations

Principal Differential Analysis deals with functional data. The word functional data refers to a collection of curves that are independent and measured on a dense grid of time points in an interval. These time points can be equally or unequally spaced. A differential equation is believed capable of capturing the features of these n curves.

Ramsay(1996) first introduced Principal Differential Analysis (PDA) as an alternative to the Principal Component Analysis(PCA). PDA finds a linear differential equation that captures features of a collection of curves, in order to have a low dimensional approximation for functional data. PDA is based on the …

Distributional Properties Of Inversions And Segmentation Algorithms For Rna Sequences, Sameera Dhananjaya Viswakula

Open Access Theses & Dissertations

Ribonucleic acid (RNA) is a long single stranded molecule made up of four types of nucleotide bases: Adenine (A), Cytosine(C), Guanine (G) and Uracil (U). It folds back on itself and forms C-G and A-U complementary base pairs. The set of such hydrogen-bonded pairs in an RNA molecule is called its secondary structure. Knowing the secondary structure of RNA is useful for understanding its biological function. Prediction of RNA secondary structure from the nucleotide sequence has been an important bioinformatics problem for over two decades.

The work in this thesis is motivated by the need to improve the secondary structure …

Modeling And Analysis Of Repeated Ordinal Data Using Copula Based Likelihoods And Estimating Equation Methods, Raghavendra Rao Kurada

Mathematics & Statistics Theses & Dissertations

Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and finance. These data normally are analyzed using both likelihood and non-likelihood methods. The first part of this dissertation discusses the multivariate ordered probit model which is a likelihood method based on latent variables. We show that this latent variable model belong to a very general class of Copula models. We use the copula representation for the multivariate ordered probit model to obtain maximum likelihood estimates of the parameters. We apply the methodology in the analysis of real life data examples.

Though likelihood methods are preferable, there …

Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test, Michael Lance

Wayne State University Dissertations

Historically, it has been accepted practice for critical values for the Winsorized t test for independent samples to be based on adjusted degrees of freedom depending on the number of total non-Winsorized (approximate) values. Recently, a new such table of Winsorized critical values has been developed via approximate randomization by Monte Carlo simulation.

Based on eight common data distributions estimated from Psychology and Education along with the normal and five Mathematical distributions, these two tables of values were compared with respect to robustness to types I and II errors through Monte Carlo simulations for one and 10% Winsorized values per …

A Comparison Of The Effects Of Non-Normal Distributions On Tests Of Equivalence, Linda Ellington

Wayne State University Dissertations

Statistical theory and its application provide the foundation to modern systematic inquiry in the behavioral, physical and social sciences disciplines (Fisher, 1958; Wilcox, 1996). It provides the tools for scholars and researchers to operationalize constructs, describe populations, and measure and interpret the relations between populations and variables (Weinbach & Grinnell, 1997; Wilcox, 1996). Given that the majority of real data analysis in the behavioral and social sciences is comprised of non-normally distributed data, it is important that researchers be aware of the effects of non-normal distributions on the probability of detecting equivalence between populations.

The present study examined the effects …

Academic Predictors Of National Council Licensure Examination For Registered Nurses Pass Rates, Maybeth J. Elliott

Walden Dissertations and Doctoral Studies

The United States continues to be affected by a severe, long-standing nursing shortage that is not projected to resolve within the next 10 or more years. Unsuccessful passage of the National Council Licensure Examination for Registered Nurses (NCLEX-RN) among graduate nurses remains one of several key contributors to the nursing shortage. The goal of this study was to identify if either cumulative fall semester GPA; the overall prenursing science, mathematics, and English GPA; type of high school background; TOEFL score; clinical pass or fail; and on-time program completion best predicted passage of NCLEX-RN. Archived records from the academic years of …

How Other Drivers’ Vehicle Characteristics Influence Your Driving Speed, Russell Brockett

CMC Senior Theses

An analysis of the effect of passing vehicles’ characteristics and their impact on other drivers’ velocities was investigated.  Three experimental studies were proposed and likely outcomes were discussed.  Experiment 1 focused on the effect of passing vehicle type (SUV, sedan or truck) on driver speed.  Drivers were hypothesized as going faster when the same vehicle type as they were driving passed them versus when no vehicle or a different vehicle passed them.  Experiment 2 focused on the effect of passing SUV age on driver’s speed.  Evidence suggests passing older SUVs will increase the driver’s speed more than new SUVs.  Experiment …

Applying Localized Realized Volatility Modeling To Futures Indices, Luella Fu

CMC Senior Theses

This thesis extends the application of the localized realized volatility model created by Ying Chen, Wolfgang Karl Härdle, and Uta Pigorsch to other futures markets, particularly the CAC 40 and the NI 225. The research attempted to replicate results though ultimately, those results were invalidated by procedural difficulties.

Bayesian Semiparametric Generalizations Of Linear Models Using Polya Trees, Angela Schoergendorfer

University of Kentucky Doctoral Dissertations

In a Bayesian framework, prior distributions on a space of nonparametric continuous distributions may be defined using Polya trees. This dissertation addresses statistical problems for which the Polya tree idea can be utilized to provide efficient and practical methodological solutions.

One problem considered is the estimation of risks, odds ratios, or other similar measures that are derived by specifying a threshold for an observed continuous variable. It has been previously shown that fitting a linear model to the continuous outcome under the assumption of a logistic error distribution leads to more efficient odds ratio estimates. We will show that deviations …

An Analog Experiment Comparing Goal-Free Evaluation And Goal Achievement Evaluation Utility, Brandon W. Youker

Dissertations

Goal-free evaluation (GFE) is the process of determining the merit of an evaluand independent of the stated or implied goals and objectives, whereas goal achievement evaluation (GAE), as the most rudimentary form of goal-based evaluation, determines merit according to the evaluand’s level of accomplishment with regard to its goals. This study examines the utility of GAE and GFE from the perspective of the evaluation’s intended users. In the study, two evaluation teams, goal achievement and goal-free, independently and simultaneously evaluate the same human service program. Each team produced a final evaluation report, which was read by the evaluation’s users, who …

Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah

Research Collection School Of Economics

We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.

Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung

Research Collection School Of Economics

We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …

Class Discovery And Prediction Of Tumor With Microarray Data, Bo Liu

All Graduate Theses, Dissertations, and Other Capstone Projects

Current microarray technology is able take a single tissue sample to construct an Affymetrix oglionucleotide array containing (estimated) expression levels of thousands of different genes for that tissue. The objective is to develop a more systematic approach to cancer classification based on Affymetrix oglionucleotide microarrays. For this purpose, I studied published colon cancer microarray data. Colon cancer, with 655,000 deaths worldwide per year, has become the fourth most common form of cancer in the United States and the third leading cause of cancer - related death in the Western world. This research has been focuses in two areas: class discovery, …

Decision Aid Models For Resource Sharing Strategies During Global Influenza Pandemics, Alfredo Santana Reynoso

USF Tampa Graduate Theses and Dissertations

Pandemic influenza outbreaks have historically entailed significant societal and economic disruptions. Today, our quality of life is threatened by our inadequate preparedness for the imminent pandemic. The key challenges we are facing stem from a significant uncertainty in virus epidemiology, limited response resources, inadequate international collaboration, and the lack of appropriate science-based decision support tools. The existing literature falls short of comprehensive models for global pandemic spread and mitigation which incorporate the heterogeneity of the world regions and realistic travel networks. In addition, there exist virtually no studies which quantify the impact of resource sharing strategies among multiple countries. This …

Parent Involvement In Children's Schooling: An Investigation Of Measurement Equivalence Across Ethnic Groups, Heather Marie Scott

USF Tampa Graduate Theses and Dissertations

Epstein et al.'s Theory of Overlapping Spheres of Influence focuses on the interaction and communication, or partnerships, among families, schools, and the community to bring the three closer together. The theory works in conjunction with Epstein's typology of parental involvement, which focuses on six types of involvement that are instrumental to a child's development and his/her school and educational success. These serve as the framework for the study and support the construct of parent's involvement in children's schooling.

The purpose of the current study was to conduct further validation analyses of an inventory designed to measure the construct of parent …

A Novel Device For Cell-Cell Electrofusion, Justin T. Stewart

USF Tampa Graduate Theses and Dissertations

Cell transplantation therapy is a potentially powerful tool and can be used to replace defective cells with healthy cells. This offers the possibility of alleviating the destructive symptoms for many diseases such as Parkinson's disease, Alzheimer's disease, stroke, spinal cord trauma, Type I diabetes and many more. While there are many diseases that could be positively impacted from cell transplantation therapy, the focus of this research is insulin dependent, Type I Diabetes.

The Islets of Langerhans are composed of various types of cells located in the pancreas and are responsible for a variety of biochemical functions. Specifically, the beta Islet …

Statistical Analysis And Modeling: Cancer, Clinical Trials, Environment And Epidemiology., Dimitrios Vovoras

USF Tampa Graduate Theses and Dissertations

The current thesis is structured in four parts. Vector smoothing methods are used to study environmental data, in particular records of extreme precipitation, the models utilized belong to the vector generalized additive class. In the statistical analysis of observational studies the identification and adjustment for prognostic factors is an important component of the analysis; employing flexible statistical methods to identify and characterize the effect of potential prognostic factors in a clinical trial, namely "generalized additive models", presents an alternative to the traditional linear statistical model. The classes of models for which the methodology gives generalized additive extensions include grouped survival …

Statistical Models For Environmental And Health Sciences, Yong Xu

USF Tampa Graduate Theses and Dissertations

Statistical analysis and modeling are useful for understanding the behavior of different phenomena. In this study we will focus on two areas of applications: Global warming and cancer research. Global Warming is one of the major environmental challenge people face nowadays and cancer is one of the major health problem that people need to solve.

For Global Warming, we are interest to do research on two major contributable variables: Carbon dioxide (CO2) and atmosphere temperature. We will model carbon dioxide in the atmosphere data with a system of differential equations. We will develop a differential equation for each of six …

Alternative Statistical Methods For Analyzing Geological Phenomena: Bridging The Gap Between Scientific Disciplines, Joseph Frank Van Gaalen

USF Tampa Graduate Theses and Dissertations

When we consider the nature of the scientific community in conjunction with a sense of typical economic circumstances we find that there are two distinct paths for development. One path involves hypothesis testing and evolution of strategies that are linked with iterations in equipment advances. A second, more complicated scenario, can involve external influences whether economic, political, or otherwise, such as the government closure of NASA's space program in 2011 which will no doubt influence research in associated fields. The following chapters are an account of examples of two statistical techniques and the importance of both on the two relatively …