Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence,
2019
Central Washington University
Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson
All Master's Theses
Artiodactyl bones are the most common faunal remains found in Washington prehistoric archaeology sites, but they are often too fragmented to accurately identify a family, genus, or species. Traditional faunal analysis can only organize unidentifiable bone fragments into size class, and chemical methods often require the destruction of bone samples. In this thesis research, I tested a new, nondestructive faunal analysis technique using portable X-ray fluorescence (pXRF) to measure trace element concentrations in comparative collection and archaeological bone samples. Using cannonbones from five different artiodactyl species, I collected trace element data from 50 comparative collection specimens and 18 archaeological specimens …
Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood,
2019
Georgia Southern University
Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya
College of Graduate Studies: Theses & Dissertations
Variable selection is one of the standard ways of selecting models in large scale datasets. It has applications in many fields of research study, especially in large multi-center clinical trials. One of the prominent methods in variable selection is the penalized likelihood, which is both consistent and efficient. However, the penalized selection is significantly challenging under the influence of random (frailty) covariates. It is even more complicated when there is involvement of censoring as it may not have a closed-form solution for the marginal log-likelihood. Therefore, we applied the penalized quasi-likelihood (PQL) approach that approximates the solution for such a …
Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials,
2019
Georgia Southern University
Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials, Victor Chukwu
College of Graduate Studies: Theses & Dissertations
In Clinical Practice, combination drug therapy has become common in treating many disease conditions. The purpose of these combinations is often to ensure optimal efficacy and to reduce adverse effects that may arise from monotherapy. Clinical trials have also been conducted to ensure efficacy and safety of these combinations before they are introduced into the market. However, adverse effects still occur with combination therapies. The objective of this study is to (1) To determine a region of optimum doses of Drug A and Drug B in combination while focusing on efficacy alone (2) To determine a region of optimum doses …
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications,
2019
Georgia Southern University
Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem
College of Graduate Studies: Theses & Dissertations
In this thesis, new generalized distributions, namely Beta Lindley-Log-Logistic (BLLLoG) distribution, Marshall-Olkin Lindley-Weibull (MOLW) distribution, and Gamma LindleyWeibull (GLW) distribution as well as related sub-distributions are proposed. Series expansion of the densities are obtained. Statistical properties of these distributions, including hazard function, reverse hazard function, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived. Method of maximum likelihood is used to estimate the parameters of the new distributions. Monte Carlo simulation is employed to examine the performance of the proposed distributions. Applications of the generalized distributions to real lifetime data are presented to …
Composite Nonparametric Tests In High Dimension,
2019
University of Kentucky
Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos
Theses and Dissertations--Statistics
This dissertation focuses on the problem of making high-dimensional inference for two or more groups. High-dimensional means both the sample size (n) and dimension (p) tend to infinity, possibly at different rates. Classical approaches for group comparisons fail in the high-dimensional situation, in the sense that they have incorrect sizes and low powers. Much has been done in recent years to overcome these problems. However, these recent works make restrictive assumptions in terms of the number of treatments to be compared and/or the distribution of the data. This research aims to (1) propose and investigate refined …
A Flexible Zero-Inflated Poisson Regression Model,
2019
University of Kentucky
A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele
Theses and Dissertations--Statistics
A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mixtures of regressions models for flexible mixture modeling, we propose a …
Characterizations Of Certain Recently Introduced Discrete Distributions,
2019
Marquette University
Characterizations Of Certain Recently Introduced Discrete Distributions, Gholamhossein G. Hamedani
Mathematics, Statistics and Computer Science Faculty Research and Publications
Characterizations of certain recently introduced discrete distributions are presented to complete, in some way, the works cited in the References.
Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers,
2019
Walden University
Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers, Kimala Proctor
Walden Dissertations and Doctoral Studies
Research indicates that the current teacher shortage is in part due to stress and burnout. A topic that has not been examined is beginning expatriate English medium teachers (EMTs) with 5 years or less of teaching experience in the United Arab Emirates and the relationship between using individualized, self-initiated wellness paradigms and stress, job burnout, and intent to leave the teaching profession. The transactional model of stress and coping, Maslach's multidimensional theory of burnout, and the health promotion model were used to evaluate the moderating effects of the EMTs' burnout and stress levels on their wellness and intent to leave. …
Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach,
2019
Georgia Southern University
Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman
Psychology: Faculty Publications
Surveys commonly suffer from insufficient effort responding (IER). If not accounted for, IER can cause biases and lead to false conclusions. In particular, Cronbach’s alpha has been empirically observed to either deflate or inflate due to IER. This paper will elucidate how IER impacts Cronbach’s alpha in a variety of situations. Previous results concerning internal consistency under mixture models are extended to obtain a characterization of Cronbach’s alpha in terms of item validities, average variances, and average covariances. The characterization is then applied to contaminating distributions representing various types of IER. The discussion will provide commentary on previous simulation-based investigations, …
Cubic Rank Transmuted Modified Burr Iii Pareto Distribution: Development, Properties, Characterizations And Applications,
2019
National College of Business Administration and Economic
Cubic Rank Transmuted Modified Burr Iii Pareto Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Wenhui Sheng, Munir Ahmad
Mathematical and Statistical Science Faculty Research and Publications
In this paper, a flexible lifetime distribution called Cubic rank transmuted modified Burr III-Pareto (CRTMBIII-P) is developed on the basis of the cubic ranking transmutation map. The density function of CRTMBIII-P is arc, exponential, left-skewed, right-skewed and symmetrical shaped. Descriptive measures such as moments, incomplete moments, inequality measures, residual life function and reliability measures are theoretically established. The CRTMBIII-P distribution is characterized via ratio of truncated moments. Parameters of the CRTMBIII-P distribution are estimated using maximum likelihood method. The simulation study for the performance of the maximum likelihood estimates (MLEs) of the parameters of the CRTMBIII-P distribution is carried out. …
On Burr Iii-Pareto Distribution: Development, Properties, Characterizations And Applications,
2019
National College of Business Administration and Economic
On Burr Iii-Pareto Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Mustafa Ç. Korkmaz, Munir Ahmad
Mathematical and Statistical Science Faculty Research and Publications
In this paper, a new four parameter lifetime model with increasing, decreasing, increasing-decreasing, decreasing-increasing-decreasing, modified bathtub, bathtub and inverted bathtub hazard rate function called Burr III-Pareto (BIII-Pareto) is developed on the basis of the T-X family technique. The BIII-Pareto density function is arc, J-shape, reverse J-shape, positively, negatively skewed and symmetrical. Some structural and mathematical properties including moments, moments of order statistics, inequality measures and reliability measures are theoretically established. The BIII-Pareto distribution is characterized via different techniques. Parameters of the BIII-Pareto distribution are estimated using maximum likelihood method. The simulation study for performance of the maximum likelihood estimates (MLEs) …
On Burr Iii Marshal Olkin Family: Development, Properties, Characterizations And Applications,
2019
National College of Business Administration and Economic
On Burr Iii Marshal Olkin Family: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Mustafa Ç. Korkmaz, Gauss M. Cordeiro, Haitham M. Yousof, Munir Ahmad
Mathematical and Statistical Science Faculty Research and Publications
In this paper, a flexible family of distributions with unimodel, bimodal, increasing, increasing and decreasing, inverted bathtub and modified bathtub hazard rate called Burr III-Marshal Olkin-G (BIIIMO-G) family is developed on the basis of the T-X family technique. The density function of the BIIIMO-G family is arc, exponential, left- skewed, right-skewed and symmetrical shaped. Descriptive measures such as quantiles, moments, incomplete moments, inequality measures and reliability measures are theoretically established. The BIIIMO-G family is characterized via different techniques. Parameters of the BIIIMO-G family are estimated using maximum likelihood method. A simulation study is performed to illustrate the performance of the …
The Nested Joint Clustering Via Dirichlet Process Mixture Model,
2019
University of Wisconsin - Milwaukee
The Nested Joint Clustering Via Dirichlet Process Mixture Model, Shengtong Han, Hongmei Zhang, Wenhui Sheng, Hasan Arshad
Mathematical and Statistical Science Faculty Research and Publications
This article focuses on the clustering problem based on Dirichlet process (DP) mixtures. To model both time invariant and temporal patterns, different from other existing clustering methods, the proposed semi-parametric model is flexible in that both the common and unique patterns are taken into account simultaneously. Furthermore, by jointly clustering subjects and the associated variables, the intrinsic complex shared patterns among subjects and among variables are expected to be captured. The number of clusters and cluster assignments are directly inferred with the use of DP. Simulation studies illustrate the effectiveness of the proposed method. An application to wheal size data …
Modeling Correlated Data Via Copulas,
2019
University of Texas at El Paso
Modeling Correlated Data Via Copulas, Panfeng Liang
Open Access Theses & Dissertations
Copulas are widely used to model the dependency structure among components of multi- variate data sets. Elliptical copulas, such as Gaussian copula, are most popular copulas being used since many data sets follow elliptical distributions or meta-elliptical distribu- tions (Fang et al. (2002)). However, today's approaches and software packages require us to assume the specific category, such as Gaussian or Student's T, of the elliptical cop- ula before estimating it. In this Thesis, we will propose a Bayesian method using Markov chain Monte Carlo (MCMC) methods to estimate the density function of elliptical copulas without specifying it is the copula …
Bayesian Analysis Of Variable-Stress Accelerated Life Testing,
2019
University of Texas at El Paso
Bayesian Analysis Of Variable-Stress Accelerated Life Testing, Richard Okine
Open Access Theses & Dissertations
Several authors have over the years studied the art of modeling data from accelerated life testing and making inferences from such data. In this study, we consider a continuously varying stress accelerated life testing procedure which is the limiting case of the multiple stress-level discussed by Doksum and H´oyland [1]. We derive the likelihood function for the life distribution of the continuously increasing stress accelerated life testing model and consequently the Fisher's Information Matrix. We propose a Bayesian analysis for this distribution using the Gibbs Sampling Procedure. We conduct simulation studies and real data analysis to demonstrate the efficiency of …
Application Of Urinary Metabolites For Cancer Detection,
2019
University of Texas at El Paso
Application Of Urinary Metabolites For Cancer Detection, Qin Gao
Open Access Theses & Dissertations
Prostate cancer (PCa) is the 3rd most common cause of male cancer mortality in the US. Early diagnosis and treatment of PCa will improve the quality of care and reduce mortality. The prostate specific antigen (PSA) is commonly used in the current PCa screening, but its limitation has resulted in an intense search for more reliable biomarkers. Studies showed that dogs could differentiate PCa patients from negative control by sniffing their urine. As the odor profiles are generated by volatile organic compounds (VOCs), the finding suggests that particular VOCs could be linked to PCa, PCa risk levels and other cancers. …
Confidence Intervals For The Expected P-Value,
2019
University of Texas at El Paso
Confidence Intervals For The Expected P-Value, Emmanuel Kofi Abrefa
Open Access Theses & Dissertations
The p-value is widely used in many application fields. In common practice, a scientific finding is deemed statistically significant if its resultant p-value is less than a pre-specified significance level, for example α = 0.05, albeit many statistically significant results are not reproducible in new studies. Mixed reasons including misuses, abuses, misunderstanding and misinterpretation arouse intensive debates and conservatives around the p-value from time to time over the years. Yet no reasonable solutions have been proposed. In this research, we make efforts to close the gap by advocating the use of confidence level for the expected p-value p0. This allows …
Robust Statistical Inference For The Gaussian Distribution,
2019
University of Texas at El Paso
Robust Statistical Inference For The Gaussian Distribution, Andrews Tawiah Anum
Open Access Theses & Dissertations
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by outliers or observations that are not representative of the underlying "true" data generating process. This thesis focuses on an estimator with this characteristic. The divergence function is introduced in Chapter 2 with the sole aim of taking the function f to be the univariate normal distribution and α - [0, 1]. The estimator fails when we rely on the classic Newton's method to converge to the minimum of the density power divergence (MDPD) function. There is a tendency of such estimator never to approach …
Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks,
2019
University of Texas at El Paso
Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks, Jazmin Quezada
Open Access Theses & Dissertations
A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks,- also called Artificial Neural Networks - are a variety of deep learning technology, which also falls under the umbrella of artificial intelligence, or AI. Recent studies shows that Artificial Neural Network has the highest coefficient of determination (i.e. measure to assess how well a model explains and predicts future outcomes.) in comparison to the K-nearest neighbor classifiers, logistic regression, discriminant analysis, naive Bayesian classifier, and classification trees. In this work, the theoretical description of the neural network methodology …
On The Performance Of Variable Selection And Classification Via Rank-Based Classifier,
2019
University of Texas at El Paso
On The Performance Of Variable Selection And Classification Via Rank-Based Classifier, Md Showaib Rahman None Sarker
Open Access Theses & Dissertations
In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), various methods have been proposed in the literature. But only few of them take into account correlation patterns and grouping effects among the genes. In this article, we propose a rank-based modification of the popular penalized logistic regression procedure based on a combination of l1 and l2 penalties capable of handling possible correlation among genes in different groups. While the l1 penalty maintains sparsity, the …
