Statistics and Probability Commons^™

Exponential And Hypoexponential Distributions: Some Characterizations, George Yanev

School of Mathematical & Statistical Sciences Faculty Publications

The (general) hypoexponential distribution is the distribution of a sum of independent exponential random variables. We consider the particular case when the involved exponential variables have distinct rate parameters. We prove that the following converse result is true. If for some n ≥ 2, X1, X2, . . . , Xn are independent copies of a random variable X with unknown distribution F and a specific linear combination of Xj ’s has hypoexponential distribution, then F is exponential. Thus, we obtain new characterizations of the exponential distribution. As corollaries of the main results, we extend some previous characterizations established recently …

The Local Stability Of A Modified Multi-Strain Sir Model For Emerging Viral Strains, Miguel Fudolig, Reka Howard

Department of Statistics: Faculty Publications

We study a novel multi-strain SIR epidemic model with selective immunity by vaccination. A newer strain is made to emerge in the population when a preexisting strain has reached equilbrium. We assume that this newer strain does not exhibit cross-immunity with the original strain, hence those who are vaccinated and recovered from the original strain become susceptible to the newer strain. Recent events involving the COVID-19 virus shows that it is possible for a viral strain to emerge from a population at a time when the influenza virus, a well-known virus with a vaccine readily available, is active in a …

Can Statcast Variables Explain The Variation In Weighted Runs Created Plus?, Ryan Kupiec

Student Research

The release of Statcast data in 2015 was revolutionary for data analysis in the game of baseball. Many analysts have begun using this data regularly, but none have used it exclusively. Often older, less reliable statistics (on-base percentage) are still used in favor of the newer statistics (weighted runs created plus). In this paper, we attempt to explain the variation in weighted runs created plus (wRC+) using Statcast variables such as exit velocity and launch angle. We find that exit velocity along with other Statcast variables, can explain as much as 70% of the variation in wRC+. Launch angle can …

Confirmative Evaluation: New Cipp Evaluation Model, Tia L. Finney

Journal of Modern Applied Statistical Methods

Struggling trainees often require a substantial investment of time, effort, and resources from medical educators. An emergent challenge involves developing effective ways to accurately identify struggling students and better understand the primary causal factors underlying their poor performance. Identifying the potential reasons for poor performance in medical school is a key first step in developing suitable remediation plans. The SOM Modified Program is a remediation program that aims to ensure academic success for medical students. The purpose of this study is to determine the impact of modifying the CIPP evaluation model by adding a confirmative evaluation step to the model. …

Cellphone Laws And Teens' Calling While Driving: Analysis Of Repeated Cross-Sectional Surveys In 2013, 2015, 2017, And 2019, Li Li, Caitlin N. Pope, Rebecca R. Andridge, Julie K. Bower, Guoqing Hu, Motao Zhu

Graduate Center for Gerontology Faculty Publications

BACKGROUND: Distracted driving among teens is a public health and safety concern. Most states in the U.S. have sought to restrict cellphone use while driving by enacting laws. This study examines the difference in prevalence of self-reported calling while driving (CWD) between states with different cellphone bans.

METHODS: Demographics and CWD data were extracted from state Youth Risk Behavior Surveys (YRBS) from 14 states in 2013, 2015, 2017, and 2019. The state YRBS is conducted every 2 years with a representative sample of 9th through 12th grade students attending public school. States were grouped by type of cellphone law(s): no …

Principal Component Analysis For Predicting The Party Of The Legislators, Afsana Mimi

Publications and Research

In Spring 2020, I did a project, "Decision Tree Predicting the Party of Legislators," and construct a decision tree model to predict legislators' parties' based on their votes. We also use this model to identify legislators who frequently voted against their parties. We used the legislators' roll call votes, Office of Clerk U.S. House of Representatives Data Sets (Categorical values) collected in 2018 and 2019. In this new project, We study the 2018 and 2019 vote data using Principal Component Analysis (PCA). The goal is to find a (compressed) model using unsupervised learning to distinguish the legislators' parties, and PCA …

The Effect Of Area Deprivation On Covid-19 Risk In Louisiana, Madhav Kc, Evrim Oral, Susanne Straif-Bourgeois, Ariane L. Rung, Edward S. Peters

School of Public Health Faculty Publications

Background Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana. Methods The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The …

A Brief On Optimal Transport, Austin G. Vandegriffe

Graduate Student Research & Creative Works

Optimal transport is an interesting and exciting application of measure theory to optimization and analysis. In the following, I will bring you through a detailed treatment of random variable couplings, transport plans, basic properties of transport plans, and finishing with the Wasserstein distance on spaces of probability measures with compact support. No detail is left out in this presentation, but some results have further generality and more intricate consequences when tools like measure disintegration are used. But this is left for future work.

A Brief On Characteristic Functions, Austin G. Vandegriffe

Graduate Student Research & Creative Works

Characteristic functions (CFs) are often used in problems involving convergence in distribution, independence of random variables, infinitely divisible distributions, and stochastics. The most famous use of characteristic functions is in the proof of the Central Limit Theorem, also known as the Fundamental Theorem of Statistics. Though less frequent, CFs have also been used in problems of nonparametric time series analysis and in machine learning. Moreover, CFs uniquely determine their distribution, much like the moment generating functions (MGFs), but the major difference is that CFs always exists, whereas MGFs can fail, e.g. the Cauchy distribution. This makes CFs more robust in …

Uganda As A Role Model For Pandemic Containment In Africa, Ahmed M. Sarki, Alex Ezeh, Saverio Stranges

Epidemiology and Biostatistics Publications

No abstract provided.

The Impact Of The Diabetes Management Incentive On Diabetes-Related Services: Evidence From Ontario, Canada., Thaksha Thavam, Rose Anne Devlin, Amardeep Thind, Gregory S Zaric, Sisira Sarma

Epidemiology and Biostatistics Publications

Financial incentives have been introduced in several countries to improve diabetes management. In Ontario, the most populous province in Canada, a Diabetes Management Incentive (DMI) was introduced to family physicians practicing in patient enrollment models in 2006. This paper examines the impact of the DMI on diabetes-related services provided to individuals with diabetes in Ontario. Longitudinal health administrative data were obtained for adults diagnosed with diabetes and their family physicians. The study population consisted of two groups: DMI group (patients enrolled with a family physician exposed to DMI for 3 years), and comparison group (patients affiliated with a family physician …

Participatory Video As A Novel Recovery-Oriented Intervention In Early Psychosis: A Pilot Study., Arlene G Macdougall, Sahana Kukan, Elizabeth Price, Sarah Glen, Richelle Bird, Laura Powe, Joshua C. Wiener, Paul H Lysaker, Kelly K Anderson, Ross Mg Norman

Epidemiology and Biostatistics Publications

BACKGROUND: Personal narrative plays an important role in the process of recovery from psychotic illnesses. Participatory video is a novel, active intervention that can be used as a tool for fostering narrative development among people with psychosis.

AIM: To assess the feasibility, acceptability and potential clinical utility of participatory video as an innovative tool for promoting recovery in early psychosis.

METHODS: Ten outpatients of an early psychosis intervention programme were recruited to participate in 13 biweekly workshops to plan, film and produce documentary-style videos of their experiences. Feasibility was measured through recruitment and retention. Acceptability was measured through workshop attendance …

Comparative Evaluation Of Statistical Dependence Measures, Eman Abdel Rahman Ibrahim

Graduate Theses and Dissertations

Measuring and testing dependence between random variables is of great importance in many scientific fields. In the case of linearly correlated variables, Pearson’s correlation coefficient is a commonly used measure of the correlation strength. In the case of nonlinear correlation, several innovative measures have been proposed, such as distance-based correlation, rank-based correlations, and information theory-based correlation. This thesis focuses on the statistical comparison of several important correlations, including Spearman’s correlation, mutual information, maximal information coefficient, biweight midcorrelation, distance correlation, and copula correlation, under various simulation settings such as correlative patterns and the level of random noise. Furthermore, we apply those …

Modified-Half-Normal Distribution And Different Methods To Estimate Average Treatment Effect., Jingchao Sun

Electronic Theses and Dissertations

This dissertation consists of three projects related to Modified-Half-Normal distribution and causal inference. In my first project, a new distribution called Modified-Half-Normal distribution was introduced. I explored a few of its distributional properties, the procedures for generating random samples based on Bayesian approaches, and the parameter estimation based on the method of moments. The second project deals with the problem of selection bias of average treatment effect (ATE) if we use the observational data. I combined the propensity score based inverse probability of treatment weighting (IPTW) method and the directed acyclic graph (DAG) to solve this problem. The third project …

Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das

Electronic Theses and Dissertations

Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …

Aspects Of Causal Inference., John A. Craycroft

Electronic Theses and Dissertations

Observational studies differ from experimental studies in that assignment of subjects to treatments is not randomized but rather occurs due to natural mechanisms, which are usually hidden from researchers. Yet objectives of the two studies are frequently the same: identify the causal – rather than merely associational – relationship between some treatment or exposure and an outcome. The statistical issues that arise in properly analyzing observational data for this goal are numerous and fascinating, and these issues are encompassed in the domain of causal inference. The research presented in this dissertation explores several distinct aspects of causal inference. This dissertation …

Developing A Tourism Opportunity Index Regarding The Prospective Of Overtourism In Nepal, Susan Phuyal

Graduate Theses/Dissertations

This research explores Nepal's overtourism scenario based on the capacity of a locality to manage sustainable tourism practices. Environmental degradation, local infrastructure degradation, negative tourist experience and local resident responses regarding visitors are the four main variables used in this study to analyze overtourism. In order to analyze the case study of overtourism, we select the three top touristic cities of Nepal, Kathmandu, Pokhara, and Chitwan based on the number of annual visitors. Nepal's case analysis of overtourism conditions reviews the overall threat of over-tourism and establishes a metric by which tourism can be viewed as potentially detrimental to sustainability. …

Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek

Graduate Theses and Dissertations

Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear models, …

Development Of An Effect Size To Classify The Magnitude Of Dif In Dichotomous And Polytomous Items, James D. Weese

Graduate Theses and Dissertations

A standardized effect size for the SIBTEST/POLYSIBTEST procedure is proposed, allowing for Differential Item Functioning (DIF) to be classified with a single set of DIF heuristics regardless of whether data are dichotomous or polytomous. This proposed standardized effect size accounts for both variability in responses and whether participants are included in the SIBTEST/POLYSIBTEST calculations. First, a new set of unstandardized effect size heuristics are established for dichotomous data that are more aligned with Educational Testing Service (ETS) standards using two and three parameter logistic (2PL and 3PL) models. Second, a standardized effect size is proposed and compared to other DIF …

Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, Shanshan Zhang

Graduate Theses and Dissertations

Over the past years, efforts have been devoted to the genome-wide analysis of genetic and epigenetic profiles to better understand the underlying biological mechanisms of complex diseases such as cancer. It is of great importance to unravel the complex dependence structure between biological factors, and many conditional dependence tests have been developed to meet this need. The traditional partial correlation method can only capture the linear partial correlation, but not the nonlinear correlation. To overcome this limitation, we propose to use the innovative conditional distance correlation (CDC), which measures the conditional dependence between random vectors and detect nonlinear relations. In …

Survival Analysis: An Exact Method For Rare Events, Kristina Reutzel

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Conventional asymptotic methods for survival analysis work well when sample sizes are at least moderately sufficient. When dealing with small sample sizes or rare events, the results from these methods have the potential to be inaccurate or misleading. To handle such data, an exact method is proposed and compared against two other methods: 1) the Cox proportional hazards model and 2) stratified logistic regression for discrete survival analysis data.

Statistics Of Branched Populations Split Into Different Types, Thierry E. Huillet

Applications and Applied Mathematics: An International Journal (AAM)

Some population is made of n individuals that can be of P possible species (or types) at equilibrium. How are individuals scattered among types? We study two random scenarios of such species abundance distributions. In the first one, each species grows from independent founders according to a Galton-Watson branching process. When the number of founders P is either fixed or random (either Poisson or geometrically-distributed), a question raised is: given a population of n individuals as a whole, how does it split into the species types? This model is one pertaining to forests of Galton-Watson trees. A second scenario that …

Nonparametric M-Regression With Scale Parameter For Functional Dependent Data, Mebsout Mokhtaria, Attouch M. Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study the equivariant nonparametric robust regression estimation relationship between a functional dependent random covariable and a scalar response. We consider a new robust regression estimator when the scale parameter is unknown. The consistency result of the proposed estimator is studied, namely the uniform almost complete convergence (with rate). Thus, suitable topological considerations are needed, implying changes in the convergence rates, which are quantified by entropy considerations. The benefits of considering robust estimators are illustrated on two real data sets where the robust fit reveals the presence of influential outliers.

Nonparametric Estimation Of Trend Function For Stochastic Differential Equations Driven By A Weighted Fractional Brownian Motion, Abdelmalik Keddi, Fethi Madani, Amina A. Bouchentouf

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we consider the problem of nonparametric estimation of trend function for stochastic differential equations driven by a weighted fractional Brownian motion (weighted-fBm). Under some general conditions, the consistent uniform, the rate of convergence as well as the asymptotic normality of our estimator are established. In addition, a numerical example is provided to illustrate the validity of the considered estimator.

Impatient Customers In An Markovian Queue With Bernoulli Schedule Working Vacation Interruption And Setup Time, P. Manoharan, T. Jeeva

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, using probability generating function method, Impatient customers in an Markovian queue with Bernoulli schedule working vacation interruption and setup time is discussed. Customers impatience is due to the servers vacation. During the working vacation period, if there are customers in the queue, the vacation can be interrupted at a service completion instant and the server begins a regular service period with probability (1 - b) or continues the vacation with probability b. We obtain the probability generating functions of the stationary state probabilities, performance measures, sojourn time of a customer and stochastic decomposition of the queue length, …

On A Multiserver Queueing System With Customers’ Impatience Until The End Of Service Under Single And Multiple Vacation Policies, Mokhtar Kadi, Amina A. Bouchentouf, Lahcene Yahiaoui

Applications and Applied Mathematics: An International Journal (AAM)

This paper deals with a multiserver queueing system with Bernoulli feedback and impatient customers (balking and reneging) under synchronous multiple and single vacation policies. Reneged customers may be retained in the system. Using probability generating functions (PGFs) technique, we formally obtain the steady-state solution of the proposed queueing system. Further, important performance measures and cost model are derived. Finally, numerical examples are presented.

The Odd Inverse Rayleigh Family Of Distributions: Simulation & Application To Real Data, Saeed E. Hemeda, Muhammad A. Ul Haq

Applications and Applied Mathematics: An International Journal (AAM)

A new family of inverse probability distributions named inverse Rayleigh family is introduced to generate many continuous distributions. The shapes of probability density and hazard rate functions are investigated. Some Statistical measures of the new generator including moments, quantile and generating functions, entropy measures and order statistics are derived. The Estimation of the model parameters is performed by the maximum likelihood estimation method. Furthermore, a simulation study is used to estimate the parameters of one of the members of the new family. The data application shows that the new family models can be useful to provide better fits than other …

Estimating Parameter Of The Selected Uniform Population Under The Generalized Stein Loss Function, K. R. Meena, Aditi K. Gangopadhyay

Applications and Applied Mathematics: An International Journal (AAM)

This paper deals with the problem of estimating scale parameter of the selected uniform population when sample sizes are unequal. The loss has been measured by the generalized Stein loss (GSL) function. The uniformly minimum risk unbiased (UMRU) estimator is derived, and the natural estimators are also constructed under the GSL function. One of the natural estimators is proved to be the generalized Bayes estimator with respect to a noninformative prior. For k = 2, we obtained a sufficient condition for an inadmissibility result and demonstrate that the natural estimator and UMRU estimator are inadmissible. A simulation investigation is also …

Analysis Of Map/Ph/1 Queueing Model With Breakdown, Instantaneous Feedback And Server Vacation, G. Ayyappan, K. Thilagavathy

Applications and Applied Mathematics: An International Journal (AAM)

In this article, we analyze a single server queueing model with feedback, a single vacation under Bernoulli schedule, breakdown and repair. The arriving customers follow the Markovian Arrival Process (MAP) and service follow the phase-type distribution. When the server returns from vacation, if there is no one present in the system, the server will wait until the customer’s arrival. When the service completion epoch if the customer is not satisfied then that customer will get the service immediately. Under the steady-state probability vector that the total number of customers are present in the system is probed by the Matrix-analytic method. …

On A New Class Of Bivariate Survival Distributions Based On The Model Of Dependent Lives And Its Generalization, Shirin Shoaee

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, a new class of survival distributions based on the model of dependent lives and proportional hazard rate family is introduced. This new family of bivariate survival models contains several bivariate lifetime models and is more flexible. The main purpose of this paper is to generalize this family of bivariate survival distributions of dependent lives so that more flexible models can be achieved. These new families of distributions are called the bivariate proportional hazard rate (BPHR) and the bivariate proportional hazard rate-geometric (BPHRG) families, respectively. It is also observed that, if θ = 1, then the BPHR family …