Statistics and Probability Commons^™

Transportation Of Perishable And Refrigerated Foods In Mylar Foil Bags And Insulated Containers: A Time-Temperature Study, Yanyan Li, John P. Schrade, Haiyan Su, John Specchio

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Data are lacking on the temperature changes of food during transport without the use of refrigerated trucks. The purpose of this study was to evaluate the ability of several insulated and noninsulated containers with or without frozen gel packs to keep perishable and refrigerated foods within the temperature safe zone in relationship to duration of transport. The study was designed to duplicate the practices exhibited by customers purchasing perishable food products from a cash-and-carry business. Approximately 40 perishable food items were evaluated. Four types of containers were tested: a mylar foil bag, a commercial insulated bag, a generic insulated bag, …

Safety Effect Of Missouri's Strategic Highway Safety Plan: Missouri's Blueprint For Safer Roadways, Mojtaba A. Mohammadi, V. A. Samaranayake, Ghulam H. Bham

Mathematics and Statistics Faculty Research & Creative Works

This study systematically evaluated the changes in motor vehicle crashes that occurred on the Missouri Interstate highway system following the implementation of the Missouri Strategic Highway Safety Plan (MSHSP) between 2004 and 2007. The MSHSP implemented crash injury reduction strategies in enforcement, education, engineering, and public policy. Empirical Bayesian methods were commonly used to evaluate the effects of any change in safety as a result of countermeasures. This paper presents a simple new approach to evaluating the effects of Missouri's safety plans on roadway crashes. For crash data associated with traffic and roadway characteristics, negative binomial regression models were developed …

Performance Modeling And Optimization Techniques For Heterogeneous Computing, Supada Laosooksathit

Doctoral Dissertations

Since Graphics Processing Units (CPUs) have increasingly gained popularity amoung non-graphic and computational applications, known as General-Purpose computation on GPU (GPGPU), CPUs have been deployed in many clusters, including the world's fastest supercomputer. However, to make the most efficiency from a GPU system, one should consider both performance and reliability of the system.

This dissertation makes four major contributions. First, the two-level checkpoint/restart protocol that aims to reduce the checkpoint and recovery costs with a latency hiding strategy in a system between a CPU (Central Processing Unit) and a GPU is proposed. The experimental results and analysis reveals some benefits, …

Generalized Least-Squares Regressions Iii: Further Theory And Classification, Nataniel Greene

Publications and Research

This paper continues the work of this series with two results. The first is an exponential equivalence theorem which states that every generalized least-squares regression line can be generated by an equivalent exponential regression. It follows that every generalized least-squares line has an effective normalized exponential parameter between 0 and 1 which classifies the line on the spectrum between ordinary least-squares and the extremal line for a given set of data. The second result is the presentation of fundamental formulas for the generalized least-squares slope and y-intercept.

Generalized Classes Of Distributions With Applications To Income And Lifetime Data, Shujiao Huang

College of Graduate Studies: Theses & Dissertations

In this thesis, new classes of distributions namely: exponentiated Kumaraswamy-Dagum (EKD), Log-exponentiated Kumaraswamy-Dagum (Log-EKD), McDonald Log-logistic (McLLog) and Gamma-Dagum (GD) distributions are presented. A thorough and comprehensive investigation of these classes of distributions is conducted. Mathematical properties of these classes of distributions including series expansion, hazard and reverse hazard functions, moments, generating functions, mean and median deviations, Bonferroni and Lorenz curves, distribution of order statistics, moments of order statistics and entropies are presented. Estimation of parameters of these distributions via maximum likelihood technique, Fisher information and asymptotic confidence intervals are given. Maximum likelihood estimation of the parameters of the exponentiated …

Dynamic Bayesian Approaches To The Statistical Calibration Problem, Derick Lorenzo Rivers

Theses and Dissertations

The problem of statistical calibration of a measuring instrument can be framed both in a statistical context as well as in an engineering context. In the first, the problem is dealt with by distinguishing between the "classical" approach and the "inverse" regression approach. Both of these models are static models and are used to estimate "exact" measurements from measurements that are affected by error. In the engineering context, the variables of interest are considered to be taken at the time at which you observe the measurement. The Bayesian time series analysis method of Dynamic Linear Models (DLM) can be used …

Incorporating Dependence Boundaries In Simulating Associated Discrete Data, Mary E. Haynes

Theses and Dissertations

In the study of associated discrete variables, limitations on the range of the possible association measures (Pearson correlation, odds ratio, etc.) arise from the form of the joint probability function between the variables. These limitations are known as the Fréchet bounds. The bounds for cases involving associated binary variables are explored in the context of simulating datasets with a desired correlation and set of marginal probabilities. A new method for creating such datasets is compared to an existing method that uses the multivariate probit. A method for simulating associated binary variables using a desired odds ratio and known marginal probabilities …

Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little

Kinesiology, Health and Sport Studies

Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This paper explores this question by using simulated three-form planned missing data to assess analytic model convergence, parameter estimate bias, standard error bias, mean squared error (MSE), and relative efficiency (RE).Three models were examined: a one-time point, cross-sectional model with 3 constructs; a two-time point model with 3 constructs at each time point; and a three-time point, mediation …

Lost In Translation: Statistical Inference In Court, Erica Beecher-Monas

Law Faculty Research Publications

No abstract provided.

Identification Of Genomic Factors Using Family-Based Association Studies, Libo Wang

Open Access Dissertations

Genome-wide association studies become increasingly popular and important for detecting genetic associations of complex traits. However, it is well known that spurious associations could arise from statistical analysis without proper consideration of genetic relatedness of samples. Many methods have been proposed to guard against these spurious associations. Here we focus on multi-locus association studies of quantitative traits and the case-control status, and propose algorithms that take into consideration of genetic related samples to address possible confounding issues. As supervised dimension reduction methods, these algorithms performs well to conduct association studies with a large number of biomarkers but a relative small …

The Initial Phases Of A Consistent Pricing System That Reflects The Online Sale Value Of A Horse, Curran A. Prettyman

Lewis Honors College Capstone Collection

Horses are one of the most uniquely priced commodities. This document provides a solution to an industry-wide weakness of inconsistent pricing and confusion. In the following report, an evaluation of the industry flaw is presented, an econometric approach is described in full, and a solution is proposed using insight gained from a regression analysis. This report uses an econometric approach to determine the impact of hunter jumper horse qualities on internet sale prices. Data is compiled from bigeq.com for seventy-eight horses in the states of Illinois, Indiana, Kentucky, Michigan, and Ohio. A linear regression analysis for twelve variables establishes that …

Roughened Random Forests For Binary Classification, Kuangnan Xiong

Legacy Theses & Dissertations (2009 - 2024)

Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are …

A Stochastic Volatility Model With Leverage Effect And Regime Switching, Hong Jiang

Legacy Theses & Dissertations (2009 - 2024)

Modeling the volatility of asset returns is a very important study in financial economics. Among the time-varying volatility models, the Stochastic Volatility (SV) models are argued to have advantages over the autoregressive conditional heteroskedasticity (ARCH) models. The purpose of this article is to put forward a generalized and flexible Stochastic Volatility model, the Stochastic Volatility Model with Leverage Effect and Regime Switching (SVLR model), which could capture the complex features of financial time series to the most extent.

A National Study Comparing Charter And Traditional Public Schools Using Propensity Score Analysis, Jason M. Bryer

Legacy Theses & Dissertations (2009 - 2024)

Unlike their private school counterparts, charter schools receive public funding but are relieved of some of the bureaucratic and regulatory constraints of public schools in exchange for being held accountable for student performance. Studies provide mixed results with regard to charter school performance. Charter schools are, by definition, schools of choice, and this means that observational data methods are required for comparing such schools with others. In observational data contexts, simple comparisons of two groups such as traditional public and charter schools typically ignore the inherent and systematic differences between the two groups. However, given well-designed observational studies and appropriate …

The Predictive Value Of Reading Frequencies In Digital And Print Formats On Eighth Grade English Language Arts Outcomes, Victoria Carol Coyle

Legacy Theses & Dissertations (2009 - 2024)

The increased availability of technology in Western culture has resulted in an increased use of technology among adolescents in both academic and personal settings. In the U.S., adolescents use technology to communicate, access information, create and distribute products on a daily basis. More importantly, this increase in technology has resulted in many more reasons and opportunities to read. It is unclear, however if increased reading in these new digital modes are related to increased scores on traditional academic assessments. This study used an archival data set to investigate relationships that existed among self-reported reading frequencies in different modes and contexts …

Raman Spectroscopy Of Blood Serum And Cerebrospinal Fluid And Multivariate Data Analysis For Alzheimer's Disease Diagnostics, Elena Ryzhikova

Legacy Theses & Dissertations (2009 - 2024)

The efficient and accurate diagnosis at the early stages of dementia is a key moment for effective treatment and productive research to find a new ways to combat the disease. It is especially true for Alzheimer's disease (AD) for which there is no effective cure, but several treatments are known to allow slowing down the degenerative processes. Alzheimer's disease (AD) displays only non-specific clinical symptoms of mental decline for decades after the initiation and is very challenging to differentiate even at the later stages when it becomes very aggressive. Despite the great need, current diagnostic tests are unable to diagnose …

New Matching Algorithm-- : Outlier First Matching (Ofm) And Its Performance On Propensity Score Analysis (Psa) Under New Stepwise Matching Framework (Smf), Yi Sun

Legacy Theses & Dissertations (2009 - 2024)

An observational study is an empirical investigation of treatment effect when randomized experimentation is not ethical or feasible (Rosenbaum 2009). Observational studies are common in real life due to the following reasons: a) randomization is not feasible due to the ethical or financial reason; b) data are collected from survey or other resources where the object and design of the study has not been determined (e.g. retrospective study using administrative records); c) little knowledge on the given region so that some preliminary studies of observational data are conducted to formulate hypotheses to be tested in subsequent experiments. When statistical analysis …

Methods For Clustering Mixed Data, Jeanmarie L. Hendrickson

Theses and Dissertations

We give a brief introduction to cluster analysis and then propose and discuss a few methods for clustering mixed data. In particular, a model-based clustering method for mixed data based on Everitt's (1988) work is described, and we use a simulated annealing method to estimate the parameters for Everitt's model. A penalized log likelihood with the simulated annealing method is proposed as a remedy for the parameter estimates being drawn to extremes. Everitt's approach and the proposed method are compared based on their performance in clustering simulated data. We then use the penalized log likelihood method on a heart disease …

Bayesian Analysis Of Continuous Curve Functions, Wen Cheng

Theses and Dissertations

We consider Bayesian analysis of continuous curve functions in 1D, 2D and 3D spaces. A fundamental feature of the analysis is that it is invariant under a simultaneous warping/re-parameterization of all target curves, as well as translation, rotation and scale of each individual if necessary. We introduce Bayesian models based on a special curve representation named Square Root Velocity Function (SRVF) introduced by Srivastava et al. (2011, IEEE PAMI). A Gaussian process model for the SRVFs of curves is proposed, and suitable prior models such as the Dirichlet distribution are employed for modeling the warping function as a cumulative distribution …

A Generalized Inflated Poisson Distribution, Patrick Stewart

Theses, Dissertations and Capstones

Count data with excess number of zeros, ones or twos are commonly encountered in experimental situations. In this thesis we have examined one such fertility data from Sweden. The standard Poisson distribution, which is widely used to model such count data, may not provide a good fit to model women's fertility (defined as the number of children per woman in her lifetime) in a specific population due to various cultural and sociological reasons. Therefore, the usual Poisson distribution is inflated at specific values suitably, as dictated by the societal norms, to fit the available data. The data set is examined …

Scalable Collaborative Filtering Recommendation Algorithms On Apache Spark, Walker Evan Casey

CMC Senior Theses

Collaborative filtering based recommender systems use information about a user's preferences to make personalized predictions about content, such as topics, people, or products, that they might find relevant. As the volume of accessible information and active users on the Internet continues to grow, it becomes increasingly difficult to compute recommendations quickly and accurately over a large dataset. In this study, we will introduce an algorithmic framework built on top of Apache Spark for parallel computation of the neighborhood-based collaborative filtering problem, which allows the algorithm to scale linearly with a growing number of users. We also investigate several different variants …

A Statistical Fmri Model For Differential T2* Contrast Incorporating T1 And T2* Of Gray Matter, M. Muge Karaman, Iain P. Bruce, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

Relaxation parameter estimation and brain activation detection are two main areas of study in magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI). Relaxation parameters can be used to distinguish voxels containing different types of tissue whereas activation determines voxels that are associated with neuronal activity. In fMRI, the standard practice has been to discard the first scans to avoid magnetic saturation effects. However, these first images have important information on the MR relaxivities for the type of tissue contained in voxels, which could provide pathological tissue discrimination. It is also well-known that the voxels located in gray matter …

Trivial Meet And Join Within The Lattice Of Monotone Triangles, John Engbers, Adam Hammett

Mathematics, Statistics and Computer Science Faculty Research and Publications

The lattice of monotone triangles (�_n, ≼) ordered by entry-wise comparisons is studied. Let τ_min denote the unique minimal element in this lattice, and τ_max the unique maximum. The number of r-tuples of monotone triangles (τ₁...,τ_r) with minimul infimum τ_min (maximul supremum τ_max, resp.) is shown to asymptotically approach r|�_n|^r-1 as n→ ∞. Thus, with high probability this even implies that one of the τ_i is τ_min (τ_max, resp.). Higher-order error terms are also discussed.

Master Regulators, Regulatory Networks, And Pathways Of Glioblastoma Subtypes, Serdar Bozdag, Aiguo Li, Mehmet Baysan, Howard A. Fine

Mathematics, Statistics and Computer Science Faculty Research and Publications

Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype-specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the …

Hp-Daemon: HIgh PErformance DIstributed ADaptive ENergy-Efficient MAtrix-MultiplicatiOn, Li Tan, Longxiang Chen, Zizhong Chen, Ziliang Zong, Rong Ge, Dong Li

Mathematics, Statistics and Computer Science Faculty Research and Publications

The demands of improving energy efficiency for high performance scientific applications arise crucially nowadays. Software-controlled hardware solutions directed by Dynamic Voltage and Frequency Scaling (DVFS) have shown their effectiveness extensively. Although DVFS is beneficial to green computing, introducing DVFS itself can incur non-negligible overhead, if there exist a large number of frequency switches issued by DVFS. In this paper, we propose a strategy to achieve the optimal energy savings for distributed matrix multiplication via algorithmically trading more computation and communication at a time adaptively with user-specified memory costs for less DVFS switches, which saves 7.5% more energy on average than …

Efficient Detection Of Counterfeit Products In Large-Scale Rfid Systems Using Batch Authentication Protocols, Farzana Rahman, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

RFID technology facilitates processing of product information, making it a promising technology for anti-counterfeiting. However, in large-scale RFID applications, such as supply chain, retail industry, pharmaceutical industry, total tag estimation and tag authentication are two major research issues. Though there are per-tag authentication protocols and probabilistic approaches for total tag estimation in RFID systems, the RFID authentication protocols are mainly per-tag-based where the reader authenticates one tag at each time. For a batch of tags, current RFID systems have to identify them and then authenticate each tag sequentially, one at a time. This increases the protocol execution time due to …

The Transmuted Marshall-Olkin Fréchet Distribution: Properties And Applications, Ahmed Z. Afify, Gholamhossein Hamedani, Indranil Ghosh, M. E. Mead

Mathematics, Statistics and Computer Science Faculty Research and Publications

This paper introduces a new four-parameter lifetime model, which extends the Marshall-Olkin Fréchet distribution introduced by Krishna et al. (2013), called the transmuted Marshall-Olkin Fréchet distribution. Various structural properties including ordinary and incomplete moments, quantile and generating function, Rényi and q-entropies and order statistics are derived. The maximum likelihood method is used to estimate the model parameters. We illustrate the superiority of the proposed distribution over other existing distributions in the literature in modeling two real life data sets.

Characterizations Of New Modified Weibull Distribution, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Several characterizations of a New Modified Weibull distribution, introduced by Doostmoradi et al. (2014), are presented. These characterizations are based on: (i) truncated moment of a function of the random variable; (ii) the hazard function; (iii) a single function of the random variable; (iv) truncated moment of certain function of the 1st order statistic.

Recurrence Relations For Moments Of Dual Generalized Order Statistics From Weibull Gamma Distribution And Its Characterizations, M. A. W. Mahmoud, Y. Abdel-Aty, N. M. Mohamed, Gholamhossein Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this paper, we establish explicit forms and new recurrence relations satisfied by the single and product moments of dual generalized order statistics from Weibull gamma distribution (WGD). The results include as particular cases the relations for moments of reversed order statistics and lower records. We present characterizations of WGD based on (i) recurrence relation for single moments, (ii) truncated moments of certain function of the variable and (iii) hazard function.

Remarks On A Paper Of Lee And Lim, Gholamhossein Hamedani, Michael Slattery

Mathematics, Statistics and Computer Science Faculty Research and Publications

Lee and Lim (2009) state three characterizations of Loamax, exponential and power function distributions, the proofs of which, are based on the solutions of certain second order non-linear differential equations. For these characterizations, they make the following statement : "Therefore there exists a unique solution of the differential equation that satisfies the given initial conditions". Although the general solution of their first differential equation is easily obtainable, they do not obtain the general solutions of the other two differential equations to ensure their claim via initial conditions. In this very short report, we present the general solutions of these equations …