Statistics and Probability Commons^™

Quantifying The Risks Of Soil Lead In Urban Community Gardens: Sampling To Account For Spatial Variability, Lauren Elizabeth-Korgol Bugdalski

Wayne State University Theses

Urban gardening has recently gained popularity as a way to provide fresh produce and income to urban residents; however, finding suitable sites for urban gardens is challenging because of historical soil lead contamination particularly in post- industrial cities like Detroit, Michigan. Soil lead measurements from three Detroit gardens were modeled using geostatistical techniques to assess risk and alternate sampling strategies. General sampling recommendations for urban gardens were developed based on results of Monte Carlo simulations and associated risk assessment. Variograms and kriged concentration maps indicate spatial variability at scales as small as one meter, with site specific variability in spatial …

Student Fact Book, Fall 2013, Thirty-Seventh Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Semester, 2013.

Analysis Of Spatial Data, Xiang Zhang

Theses and Dissertations--Statistics

In many areas of the agriculture, biological, physical and social sciences, spatial lattice data are becoming increasingly common. In addition, a large amount of lattice data shows not only visible spatial pattern but also temporal pattern (see, Zhu et al. 2005). An interesting problem is to develop a model to systematically model the relationship between the response variable and possible explanatory variable, while accounting for space and time effect simultaneously.

Spatial-temporal linear model and the corresponding likelihood-based statistical inference are important tools for the analysis of spatial-temporal lattice data. We propose a general asymptotic framework for spatial-temporal linear models and …

James-Stein Type Compound Estimation Of Multiple Mean Response Functions And Their Derivatives, Limin Feng

Theses and Dissertations--Statistics

Charnigo and Srinivasan originally developed compound estimators to nonparametrically estimate mean response functions and their derivatives simultaneously when there is one response variable and one covariate. The compound estimator maintains self consistency and almost optimal convergence rate. This dissertation studies, in part, compound estimation with multiple responses and/or covariates. An empirical comparison of compound estimation, local regression and spline smoothing is included, and near optimal convergence rates are established in the presence of multiple covariates.

James and Stein proposed an estimator of the mean vector of a p dimensional multivariate normal distribution, which produces a smaller risk than the maximum …

An Implicit Interface Boundary Integral Method For Poisson’S Equation On Arbitrary Domains, Catherine Kublik, Nicolay M. Tanushev, Richard Tsai

Mathematics Faculty Publications

We propose a simple formulation for constructing boundary integral methods to solve Poisson’s equation on domains with smooth boundaries defined through their signed distance function. Our formulation is based on averaging a family of parameterizations of an integral equation defined on the boundary of the domain, where the integrations are carried out in the level set framework using an appropriate Jacobian. By the coarea formula, the algorithm operates in the Euclidean space and does not require any explicit parameterization of the boundaries. We present numerical results in two and three dimensions.

Models And Software Development For Interval-Censored Data, Chun Pan

Theses and Dissertations

Interval-censored time-to-event data occur naturally in studies of diseases where the symptoms are not directly observable, and periodic clinical examinations are required for detection. Due to the lack of well-established procedures, interval-censored data have been conventionally treated as right-censored data, however, this introduces bias at the first place. This dissertation focuses on methodological research and software development for interval-censored data. Specifically, it consists of three projects. The first project is to create an R package for regression analysis and survival curve estimation of interval-censored data based on several published papers by our research team. In the second project, a Bayesian …

The Complete Plus-Minus: A Case Study Of The Columbus Blue Jackets, Nathan Spagnola

Theses and Dissertations

A new hockey statistic termed the Complete Plus-Minus (CPM) was created to calculate the abilities of hockey players in the National Hockey League (NHL). This new statistic was used to analyze the Columbus Blue Jackets for the 2011-2012 season. The CPM for the Blue Jackets was created using two logistic regressions that modeled a goal being scored for and against the Blue Jackets. Whether a goal was scored for or against the team were the responses, while events on the ice were the predictors in the model. It was found that the team's poor performance was due to a weak …

Challenging The State Of The Art In Post-Introductory Statistics: Preparation, Concepts, And Pedagogy, Nathan L. Tintle, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

Faculty Work Comprehensive List

The demands for a statistically literate society are increasing, and the introductory statistics course ("Stat 101") remains the primary venue for learning statistics for the majority of high school and undergraduate students. After three decades of very fruitful activity in the areas of pedagogy and assessment, but with comparatively little pressure for rethinking the content of this course, the statistics education community has recently turned its attention to use of randomization-based methods to illustrate core concepts of statistical inference. This new focus not only presents an opportunity to address documented shortcomings in the standard Stat 101 course (for example, improving …

Polytopes Arising From Binary Multi-Way Contingency Tables And Characteristic Imsets For Bayesian Networks, Jing Xi

Theses and Dissertations--Statistics

The main theme of this dissertation is the study of polytopes arising from binary multi-way contingency tables and characteristic imsets for Bayesian networks.

Firstly, we study on three-way tables whose entries are independent Bernoulli ran- dom variables with canonical parameters under no three-way interaction generalized linear models. Here, we use the sequential importance sampling (SIS) method with the conditional Poisson (CP) distribution to sample binary three-way tables with the sufficient statistics, i.e., all two-way marginal sums, fixed. Compared with Monte Carlo Markov Chain (MCMC) approach with a Markov basis (MB), SIS procedure has the advantage that it does not require …

Moments Of Matrix Variate Skew Elliptically Contoured Distributions, Shimin Zheng, Jeff Knisley, Chunming Zhang

ETSU Faculty Works

Matrix variate skew elliptically contoured distributions generalize several classes of important distributions. This paper defines and explores matrix variate skew elliptically contoured distributions. In particular, we discuss the first two moments of the matrix variate skew elliptically contoured distributions.

Characterizations Of Exponentiated Distributions, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Various characterizations of the class of exponentiated distributions are presented. These characterizations are based on a simple relationship between two truncated moments and based on functions of the nth order statistic. The results are applied to certain well-known members of this class.

Some Remarks On Arslan’S 2011 Paper, Gholamhossein Hamedani, Hans Volkmer

Mathematics, Statistics and Computer Science Faculty Research and Publications

It is shown that the main theorem of Arslan’s paper (Theorem 2, 2011), as stated, is incorrect. Under additional conditions, we present a short proof of the corrected version of the theorem. We also give a proof of a theorem of Rao and Shanbhag (1991), employed by Arslan, without the use of the Kolmogorov Consistency Theorem.

Predictors Of Treatments Acceptable To Patients For Late-Life Depression, Gerald J. Jogerst, Shimin Zheng, Erik Vanderlip

ETSU Faculty Works

Objectives. Describe older patients’ perceptions about depression and characteristics associated with acceptance of treatments. Design. Cross-sectional study. Setting. Three primary care clinics in Iowa. Participants. Consecutive sample of 529 primary care patients. Measurements. Depression screening tool (a 9-item patient health questionnaire [PHQ-9]) and questionnaire including sociodemographic data, patient attitudes about depression, and acceptability of different treatments. Results. Mean age was 71.9 years (range 60–93 years), 314 (59%) female. Among the 529 participants, 93 (17.5%) had history of depression and 60 (11.3%) had PHQ-9 scores of 10 or greater. Participants believed depression is a disease for which they would use medication …

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. …

Sparse Ridge Fusion For Linear Regression, Nozad Mahmood

Electronic Theses and Dissertations

For a linear regression, the traditional technique deals with a case where the number of observations n more than the number of predictor variables p (n > p). In the case n < p, the classical method fails to estimate the coefficients. A solution of the problem is the case of correlated predictors is provided in this thesis. A new regularization and variable selection is proposed under the name of Sparse Ridge Fusion (SRF). In the case of highly correlated predictor, the simulated examples and a real data show that the SRF always outperforms the lasso, eleastic net, and the S-Lasso, and the results show that the SRF selects more predictor variables than the sample size n while the maximum selected variables by lasso is n size.

N-Valued Refined Neutrosophic Logic And Its Applications To Physics, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present a short history of logics: from particular cases of 2-symbol or numerical valued logic to the general case of n-symbol or numerical valued logic. We show generalizations of 2-valued Boolean logic to fuzzy logic, also from the Kleene’s and Lukasiewicz’ 3-symbol valued logics or Belnap’s 4-symbol valued logic to the most general n-symbol or numerical valued refined neutrosophic logic. Two classes of neutrosophic norm (n-norm) and neutrosophic conorm (n-conorm) are defined. Examples of applications of neutrosophic logic to physics are listed in the last section. Similar generalizations can be done for n-Valued Refined Neutrosophic Set, …

On Improvement In Estimating Population Parameter(S) Using Auxiliary Information, Florentin Smarandache, Rajesh Singh

Branch Mathematics and Statistics Faculty and Staff Publications

The purpose of writing this book is to suggest some improved estimators using auxiliary information in sampling schemes like simple random sampling and systematic sampling. This volume is a collection of five papers, written by eight coauthors (listed in the order of the papers): Manoj K. Chaudhary, Sachin Malik, Rajesh Singh, Florentin Smarandache, Hemant Verma, Prayas Sharma, Olufadi Yunusa, and Viplav Kumar Singh, from India, Nigeria, and USA. The following problems have been discussed in the book: In chapter one an estimator in systematic sampling using auxiliary information is studied in the presence of non-response. In second chapter some improved …

Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.

Screening For Elder Mistreatment Among Older Adults Seeking Legal Assistance Services, Sheryl M. Strasser, Megan Smith, Scott Weaver, Shimin Zheng, Yan Cao

ETSU Faculty Works

Introduction: The aging population is a rapidly growing demographic in the United States. Isolation, limited autonomy, and declining physical and mental health render many older adults vulnerable to elder mistreatment (EM). The purpose of this study was to assess the prevalence and correlates of EM among a sample of older adults using legal assistance services in Atlanta, Georgia.

Methods: Researchers administered surveys to consenting older adults (aged 60þ) in 5 metro Atlanta community centers that hosted legal assistance information sessions as part of the Elderly Legal Assistance Program. The surveys screened for risk factors and prevalence of EM risk using …

Stochastic Representations Of The Matrix Variate Skew Elliptically Contoured Distributions, Shimin Zheng, Chunming Zhang, Jeff Knisley

ETSU Faculty Works

Matrix variate skew elliptically contoured distributions generalize several classes of important distributions. This paper defines and explores matrix variate skew elliptically contoured distributions. In particular, we discuss two stochastic representations of the matrix variate skew elliptically contoured distributions.

Ricean Over Gaussian Modelling In Magnitude Fmri Analysis—Added Complexity With Negligible Practical Benefits, Daniel W. Adrian, Ranjan Maitra, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

It is well known that Gaussian modelling of functional magnetic resonance imaging (fMRI) magnitude time-course data, which are truly Rice distributed, constitutes an approximation, especially at low signal-to-noise ratios (SNRs). Based on this fact, previous work has argued that Rice-based activation tests show superior performance over their Gaussian-based counterparts at low SNRs and should be preferred in spite of the attendant additional computational and estimation burden. Here, we revisit these past studies and, after identifying and removing their underlying limiting assumptions and approximations, provide a more comprehensive comparison. Our experimental evaluations using Receiver Operating Characteristic (ROC) curve methodology show that …

Recent Advances In Energy-Efficient Sensor Networks, Sheikh Iqbal Ahamed, Wei Wang, Jiman Hong

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.

Concept Of Sub-Independence, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Limit theorems as well as other well-known results in probability and statistics are often based on the distributions of the sums of independent random variables. The concept of sub-independence, which is weaker than that of independence, is shown to be sufficient to yield the conclusions of these theorems and results. It also provides a measure of dissociation between two random variables which is stronger than uncorrelatedness.

Undergraduate And Graduate Teaching Assistants' Perceptions Of Their Responsibilities - Factors That Help Or Hinder, Alena Moon, Hyunyi Jung, Farshid Marbouti, Kelsey Joy Rodgers, Heidi A. Diefes-Dux

Mathematics, Statistics and Computer Science Faculty Research and Publications

Effective teaching assistants (TAs) are crucial for effective student learning. This is especially true in science, technology, engineering, and mathematics (STEM) programs, where TAs are enabling large programs to transition to more student-centered learning environments. To ensure that TAs are able to support these types of learning environments, their perspectives of training, their abilities, and other work related aspects must be understood. In this paper a survey that was created based on interviews conducted with eight TAs is discussed. The survey has four primary categories of content that are critical for understanding TAs' perspectives: (1) background, (2) motivation, (3) training, …

Cross‐Campus Collaboration: A Scientometric And Network Case Study Of Publication Activity Across Two Campuses Of A Single Institution, Jeremy Birnholtz, Shion Guha, Y. Connie Yuan, Geri Gay, Caren Heller

Mathematics, Statistics and Computer Science Faculty Research and Publications

Team science and collaboration have become crucial to addressing key research questions confronting society. Institutions that are spread across multiple geographic locations face additional challenges. To better understand the nature of cross‐campus collaboration within a single institution and the effects of institutional efforts to spark collaboration, we conducted a case study of collaboration at Cornell University using scientometric and network analyses. Results suggest that cross‐campus collaboration is increasingly common, but is accounted for primarily by a relatively small number of departments and individual researchers. Specific researchers involved in many collaborative projects are identified, and their unique characteristics are described. Institutional …

Genome-Wide Associations Of Signaling Pathways In Glioblastoma Multiforme, Serdar Bozdag, Stefan Wuchty, Alexei Vazquez, Peter O. Bauer

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background: eQTL analysis is a powerful method that allows the identification of causal genomic alterations, providing an explanation of expression changes of single genes. However, genes mediate their biological roles in groups rather than in isolation, prompting us to extend the concept of eQTLs to whole gene pathways. Methods: We combined matched genomic alteration and gene expression data of glioblastoma patients and determined associations between the expression of signaling pathways and genomic copy number alterations with a non-linear machine learning approach. Results: Expectedly, over-expressed pathways were largely associated to tag-loci on chromosomes with signature alterations. Surprisingly, tag-loci that were associated …

A Proposal For A Problem-Driven Mathematics Curriculum Framework, Judith S. Zawojewski, Marta Magiera, Richard Lesh

Mathematics, Statistics and Computer Science Faculty Research and Publications

A framework for a problem-driven mathematics curriculum is proposed, grounded in the assumption that students learn mathematics while engaged in complex problem-solving activity. The framework is envisioned as a dynamic technologicallydriven multi-dimensional representation that can highlight the nature of the curriculum (e.g., revealing the relationship among modeling, conceptual, and procedural knowledge), can be used for programmatic, classroom and individual assessment, and can be easily revised to reflect ongoing changes in disciplinary knowledge development and important applications of mathematics. The discussion prompts ideas and questions for future development of the envisioned software needed to enact such a framework.

Robust Estimation Of The Correlation Matrix Of Longitudinal Data, Mehdi Maadooliat, Mohsen Pourahmadi, Jianhua Z. Huang

Mathematics, Statistics and Computer Science Faculty Research and Publications

We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of the form Σ=DLL ^⊤ D where D is a diagonal matrix proportional to the square roots of the diagonal entries of Σ and L is a unit lower-triangular matrix determining solely the correlation matrix. The first robustness is with respect to model misspecification for the innovation variances in D, and the second is robustness to outliers in the data. The latter is handled using heavy-tailed multivariate t-distributions with unknown degrees of freedom. We …

Considerations In Designing Human-Computer Interfaces For Elderly People, Drew Williams, Mohammad Arif Ul Alam, Sheikh Iqbal Ahamed, William Chu

Mathematics, Statistics and Computer Science Faculty Research and Publications

As computing devices continue to become more heavily integrated into our lives, proper design of human-computer interfaces becomes a more important topic of discussion. Efficient and useful human-computer interfaces need to take into account the abilities of the humans who will be using such interfaces, and adapt to difficulties that different users may face – such as the difficulties that elderly users must deal with. Interfaces that allow for user-specific customization, while taking into account the multiple difficulties that older users might face, can assist the elderly in properly using these newer computing devices, and in doing so possibly achieving …

The Zografos-Balakrishnan Log-Logistic Distribution: Properties And Applications, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.