Statistics and Probability Commons^™

Towards Analytical Techniques For Optimizing Knowledge Acquisition, Processing, Propagation, And Use In Cyberinfrastructure, Leonardo Octavio Lerma

Open Access Theses & Dissertations

For many decades, there has been a continuous progress in science and engineering applications.

A large part of this progress comes from the new knowledge that researchers acquire, propagate, and use. This new knowledge has revolutionized many aspects of our life, from driving to communications to shopping.

Somewhat surprisingly, there is one area of human activity which is the least impacted by the modern technological progress: the very processes of acquiring, processing, and propagating information. When we decide where to place sensors, which algorithm to use for processing the data – we rely mostly on our own intuition and on …

Resampling-Based Multiple Comparisons For Generalized Linear Models, Josephine Sarpong Akosa

Open Access Theses & Dissertations

Diverse applications in medical and epidemiological research routinely utilize generalized linear modeling to explain the relationship between the incidence of disease and particular risk factors. Researchers' interest in such models are estimated quantities from the model such as the response probabilities, the relative risks or the odds ratios and not the model itself. Often, the simultaneous estimation of these quantities or a subset of the quantities are warranted. The results are usually reported via confidence intervals at a pre-specified level of significance. Utilizing the usual 95% pointwise confidence intervals for the simultaneous inference inflates the risk of making type I …

A New Bivariate Distribution With Applications, Sathya Amarasekara

Open Access Theses & Dissertations

We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y given X is a two-parameter Gamma (s, ν(x)), where the scale parameter depends on X. If X is assumed to be any distribution, then clearly the joint distribution is well defined in all cases. We will study this new distribution by developing all possible properties, moments, shapes and estimation of parameters with a view towards applications of the distribution to data from many random number generation methods.

A Long- And Short-Run Analysis Of Electricity Demand In Ciudad Juarez, Ericka Cecilia Mendez

Open Access Theses & Dissertations

Economic growth and appliance saturation are increasing electricity consumption in Mexico. Annual frequency data from 1990 to 2012 are utilized to develop an error correction framework that sheds light on short- and long-run electricity consumption behavior in Ciudad Juarez, a large Mexican metropolitan economy at the border with the United States. The results for this study reveal that electricity is an inelastic normal good in this market. Moreover, natural gas is found to be a weak complement to electricity. With regards to the customer base in this urban economy, population, employment, and income exercise positive and statistically significant impacts on …

Variable Selection For Cox Proportional Hazards Models Via Subtle Uprooting, Chalani S. Wijayasinghe

Open Access Theses & Dissertations

Cox proportional hazards model (Cox PH model) is heavily used in survival analysis to assess the importance of various covariates on the survival times of individuals or objects through the hazard function. This study suggests a new variables selection method for Cox PH models, under the title 'Subtle uprooting', that does variable selection and model estimation for Cox proportional hazards (PH) models simultaneously.

There are subset selection methods and shrinkage selection methods suggested in the context of Cox PH model. However the subset selection methods become infeasible in higher dimensions and the available shrinkage methods need tuning of parameters making …

Comparison Of Bayesian Nonparametric Density Estimation Methods, Adel Bedoui

Open Access Theses & Dissertations

Density estimation has a long history in statistics. There are two main approaches to density, estimation parametric and nonparametric. The first approach requires specification of a family of densities f and estimation of the unknown parameter $\theta$ using a suitable estimation method, for example, maximum likelihood estimation. This approach may be prone to bias that arises from either estimation of the parameter or from incorrect specification of the probability distribution. The second approach, does not assume a specific parametric family.

In this thesis, we implement three density estimation methods that use Bayesian nonparametric approaches utilizing Markov Chain Monte Carlo methods. …

Multiplicity Adjustments For Respecification Searches In Structural Equation Models, John Appiah Kubi

Open Access Theses & Dissertations

Structural Equation Modeling (SEM), as a statistical modeling technique, is one of the most comprehensive and flexible approaches to data analysis currently available. Its use has been increasing steadily over the past few decades. Generally, it refers to a family of

techniques that employs the analysis of covariance to establish relationships among a set of variables. It allows researchers (or users) to assess the adequacy of their hypothesized models with their sample data. Often times, in assessing their models, researchers are not

only interested in the overall fit of their model but they are also interested in knowing which proposed …

A Systematic Approach To Manage Missing Data In Pavement Management Systems, Mazin M. Al-Zou'bi

Open Access Theses & Dissertations

Pavements are an important part of the highway transportation infrastructure, accounting for the largest share of the overall investment. A tremendous amount of time and money is spent each year on the construction of new pavements, as well as on the maintenance and rehabilitation of existing pavements.

Transportation agencies use pavement management systems (PMS) for their maintenance and rehabilitation planning, programming, and budgeting. PMS are used to make decisions regarding when maintenance and rehabilitation should be applied. The systems also select what type of treatment should be applied for each pavement section in the network with clear estimations of the …

Principal Differential Analysis: Incorporating Covariates Using Kernel Smoothers, Christopher Alfred Dodoo

Open Access Theses & Dissertations

Principal Differential Analysis is a statistical technique which suggests that a given set of functional data curves can be annihilated completely when an estimated linear differential

operator (LDO) is applied (Coddington & Levinson). The novelty of residuals as forcing functions is introduced in PDA.

This thesis builds on PDA with covariates by Jin et al, 2012 by dropping the assumption that the coefficients of the linear differential operator are a product of a function in t and v; the equivalent kernel is used to estimate the coefficient functions at target values. Incorporating covariates with kernel smoothers leads to two …

Analysis Of Vehicle Interactions On Interstate Highways: Discrete Choice And Linear System Approaches, Alicia Romo

Open Access Theses & Dissertations

The research in this dissertation developed statistical and linear system models to predict driving behavior according to driver attributes, vehicle characteristics, car-following dynamics and/or driving conditions. The scope of this research was limited to the interaction of two vehicles traveling in the same direction on interstate highways.

The statistical models proposed in this research investigated the contributions of the different vehicle types on the manner and likelihood of collision. Discrete choice models were used to estimate the probability of the types of collision (rear-end, angle and sideswipe) as functions of driver attributes, striking and struck vehicle types, pre-crash driving actions …

Generalized Linear Latent Mixed Modeling Of Functional Independent Measures And Patient Outcomes, Maduranga Kasun Dassanayake

Open Access Theses & Dissertations

The Functional Independent Measure (FIM) is one of the most widely accepted functional assessment measures used in the rehabilitation community. Past research studies have investigated the relationship between place of discharge, admission FIM scores or FIM difference scores, and patients' characteristics and found relationships between those variables. However, most of these studies fail to account for the multi-layered multidimensionality of the FIM and the measurement error associated with the FIM items. This study utilizes Generalized Linear Latent Mixed Models (GLLAMM) and Structural Equation Models (SEM) to assess which patient characteristics are associated with FIM difference scores and the structural relationship …

Arma-Garch Model Applied To Exchange-Traded Funds, Rebecca Davis

Open Access Theses & Dissertations

In this paper, time-varying volatility of some of the leading exchange-traded funds are studied. The ARMA mean equation with GARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset

returns. The conditional distributions of the standardized residuals are assumed to be skew-generalized error distribution. The high kurtosis and fat tail of the returns, were captured in all the data by fitting an ARMA-GARCH model with the conditional distribution of, skew-generalized error distribution.

Furthermore, the sample cross-correlations of these significant exchange-traded funds and the corresponding financial indices they mimic were computed. The empirical conclusion was …

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 …

Assessing Measurement Invariance In The Presence Of Testlets, Luis Andres Alvarado

Open Access Theses & Dissertations

Dealing with measurement invariance has been an issue of concern in confirmatory factor analysis for many years. It is important to establish measurement invariance across groups so that instruments may be validly used in multiple groups for comparison of the mean or summative scores. Throughout the years, many studies have considered testing for measurement invariance in factor models. However, there have been no studies that assess measurement invariance when so-called testlets should be modeled in the factor analytic model. Testlets add nuisance covariation to the model which can interfere when trying to detect measurement invariance. In the past, models have …

Estimating The Effect Of Dust And Low Wind Events On Hospitalizations For Asthma While Adjusting For Hourly Levels Of Air Pollutants, Priyangi Kanchana Bulathsinhala

Open Access Theses & Dissertations

El Paso, Texas is known as one of the dust hotspots in North America. We explore the effect of dust and low wind events on asthma admissions in El Paso, Texas between 2000 and 2005. Conditional logistic regression with a case-crossover design was used to estimate the probability of hospitalization after dust and low wind events while controlling for pollutants with hourly monitor measurements, and weather. The historical functional linear model is used to incorporate the hourly pollutant measures into the regression model with a continuous lag, as an alternative to a distributed lag model based on daily averages. The …

Estimating Statistical Characteristics Under Interval Uncertainty And Constraints: Mean, Variance, Covariance, And Correlation, Ali Jalal-Kamali

Open Access Theses & Dissertations

In many practical situations, we have a sample of objects of a given type. When we measure the values of a certain quantity x for these objects, we get a sequence of values x1, . . . , xn. When the sample is large enough, then the arithmetic mean E of the values xi is a good approximation for the average value of this quantity for all the objects from this class. Other expressions provide a good approximation to statistical characteristics such as variance, covariance, and correlation.

The values xi come from measurements, and measurement is never absolutely accurate.

Often, …

Computational Methods Of Hidden Markov Models With Respect To Cpg Island Prediction In Dna Sequences, Roberto Angel Ortega

Open Access Theses & Dissertations

Hidden Markov models (HMM's) are a specific case of Markov models where, contrary to Markov chains, the observer is unaware of what state the model was in when the symbol is observed. Like Markov chains, HMM's assume that the future state of a sequence is dependent only on the current state of the sequence. The parameters associated with HMM's are transition and emission probabilities, where transition probabilities are associated with the probability of transitioning from one state to another, and emission probabilities are the probabilities associated with observing a symbol given it came from a specific state.

The structure of …

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 …

Observer-Dependent Model For Analyzing Subjective Parameters In Epidemiology, Milad Zarei

Open Access Theses & Dissertations

Although medical technologies for preventing the contagion and spread of infectious diseases have improved steadily throughout the last century, new infectious diseases are still emerging and spreading swiftly. The modeling of infectious disease spread is crucial in addressing the lack of predictive ability in epidemiology. Managing the spread of infectious diseases requires processing quantitative epidemiological data and the ability to capture the dynamics of the infectious disease in order to provide a measure of control.

In this thesis, I have introducing cognitive biases in diseases spread modeling. For the first time, to the author's knowledge, the human subjective experience has …

Identifying Influential Observations Through The Intraclass Correlation Coefficient, Angel De Jesus Davalos

Open Access Theses & Dissertations

In this thesis, we analyze the performance of adapting the DFBETA statistic for identifying influential observations on the intraclass correlation coefficient under the assumptions of the one-way random effects model. Additionally, we introduce an approach for transforming negative intraclass correlation coefficient estimation values using the method of moments estimator. We apply this method on a data set of repeated blood pressure measurements, after which we will investigate implications of identifying influential observations.

Scrap Reduction Model: By Combination Of Dmaic And Design Of Experiments, Anoop J. Randive

Open Access Theses & Dissertations

This project deals with the experimentation which took place at a cable manufacturing company. The thesis describes and summarizes the various strategies and techniques that has been applied and practiced for scrap reduction. DMAIC and Six Sigma Technology has been proven very help full in order to reduce scrap to a major extent. DMAIC help to identify areas in process where extra expense exist, identify the biggest impact factor related production expenses, introduce appropriate measurement system, optimize process and reduce production cost and time. Many issues were detected by the production, such as a lack of a unified procedure for …

The Impact Of Cartel Related Violence On Ongoing Traumatic Stress And Self-Medication In Young Adults Living Along The U.S./México Border, Thom J. Taylor

Open Access Theses & Dissertations

Ongoing Potentially Traumatic Stress (OPTS) as a result of violence and insecurity along the U.S./México border remains understudied. Many residents of the border may be both indirectly and directly exposed to potentially traumatic events on an ongoing basis, particularly in the city of Cd. Juárez, México. The present study examined the impact of the violence and insecurity on daily traumatic stress levels and the potential for self-medication via alcohol, cigarettes, and illicit drugs within Spanish speaking young adult residents and commuters to Cd. Juárez, Chihuahua, México. Participants (N = 121) completed multiple online reports of location in and travel to …

Bayesian Nonparametric Regression With A Flexible Error Term Distribution, Courtney Marie Barnes

Open Access Theses & Dissertations

Datasets often exhibit heavy tailed behavior and standard analyses are often heavily influenced by outliers. We propose a nonparametric regression model whose error term distribution is a mixture of a normal and a Student t distribution. This results in a model that is more resistant to outliers compared to a model with a normal error term.

Survey Research On Communication And Language For English Language Learners And Native English Speakers Enrolled In A College Course On Statistical Literacy, Maria Guadalupe Valenzuela

Open Access Theses & Dissertations

The purpose of this study was to examine in what ways language is a factor that affects the learning process of students in an introductory statistics class. This research used a questionnaire survey instrument called: CLASS, Communication, Language And Statistics Survey that was applied to a total of 137 college students from a large southwestern public university, 83 of these students were self-identified as native English speakers (NOELL) and 53 were self-identified as English learner speakers (ELL) and one was dropped. This research found that in statistical instruction, there are some particular differences in behavior and learning process in the …