Statistics and Probability Commons^™

The Performance Of Multilevel Structural Equation Modeling (Msem) In Comparison To Multilevel Modeling (Mlm) In Multilevel Mediation Analysis With Non-Normal Data, Thanh Vinh Pham

USF Tampa Graduate Theses and Dissertations

The mediation analysis has been used to test if the effect of one variable on another variable is mediated by the third variable. The mediation analysis answers a question of how a predictor influences an outcome variable. Such information helps to gain understanding of mechanism underlying the variation of the outcome. When the mediation analysis is conducted on hierarchical data, the structure of data needs to be taken into account. Krull and MacKinnon (1999) recommended using Multilevel Modeling (MLM) with nested data and showed that the MLM approach has more power and flexibility over the standard Ordinary Least Squares (OLS) …

Bayesian Inference On Quantile Regression-Based Mixed-Effects Joint Models For Longitudinal-Survival Data From Aids Studies, Hanze Zhang

USF Tampa Graduate Theses and Dissertations

In HIV/AIDS studies, viral load (the number of copies of HIV-1 RNA) and CD4 cell counts are important biomarkers of the severity of viral infection, disease progression, and treatment evaluation. Recently, joint models, which have the capability on the bias reduction and estimates' efficiency improvement, have been developed to assess the longitudinal process, survival process, and the relationship between them simultaneously. However, the majority of the joint models are based on mean regression, which concentrates only on the mean effect of outcome variable conditional on certain covariates. In fact, in HIV/AIDS research, the mean effect may not always be of …

Improving Service Level Of Free-Floating Bike Sharing Systems, Aritra Pal

USF Tampa Graduate Theses and Dissertations

Bike Sharing is a sustainable mode of urban mobility, not only for regular commuters but also for casual users and tourists. Free-floating bike sharing (FFBS) is an innovative bike sharing model, which saves on start-up cost, prevents bike theft, and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. Efficient management of a FFBS requires: 1) analyzing its mobility patterns and spatio-temporal imbalance of supply and demand of bikes, 2) developing strategies to mitigate such imbalances, and 3) understanding the causes of a bike getting damaged and developing strategies to minimize them. All of these …

Statistical Analysis And Modeling Of Stomach Cancer Data, Chao Gao

USF Tampa Graduate Theses and Dissertations

The objective of this study is to address some important questions associated with stomach cancer patients using the data from the Surveillance Epidemiology and End Results (SEER) program of the United States. To better understand the behavior of stomach cancer, we first perform parametric analysis for each patient group (white male, white female, African American male, African American female, other male and female) to identify the probability distribution function which can best characterize the behavior of the malignant stomach tumor sizes. We evaluate the effects of patients’ age, gender and race on the malignant stomach tumor sizes by developing quantile …

Statistical Analysis And Modeling Of Ovarian And Breast Cancer, Muditha V. Devamitta Perera

USF Tampa Graduate Theses and Dissertations

The objective of the present study is to investigate key aspects of ovarian and breast cancers, which are two main causes of mortality among women. Identification of the true behavior of survivorship and influential risk factors is essential in designing treatment protocols, increasing disease awareness and preventing possible causes of disease. There is a commonly held belief that African Americans have a higher risk of cancer mortality. We studied racial disparities of women diagnosed with ovarian cancer on overall and disease-free survival and found out that there is no significant difference in the survival experience among the three races: Whites, …

Bayesian Artificial Neural Networks In Health And Cybersecurity, Hansapani Sarasepa Rodrigo

USF Tampa Graduate Theses and Dissertations

Being in the era of Big data, the applicability and importance of data-driven models like artificial neural network (ANN) in the modern statistics have increased substantially. In this dissertation, our main goal is to contribute to the development and the expansion of these ANN models by incorporating Bayesian learning techniques. We have demonstrated the applicability of these Bayesian ANN models in interdisciplinary research including health and cybersecurity.

Breast cancer is one of the leading causes of deaths among females. Early and accurate diagnosis is a critical component which decides the survival of the patients. Including the well known ``Gail Model", …

Time Series Online Empirical Bayesian Kernel Density Segmentation: Applications In Real Time Activity Recognition Using Smartphone Accelerometer, Shuang Na

USF Tampa Graduate Theses and Dissertations

Time series analysis has been explored by the researchers in many areas such, as statistical research, engineering applications, medical analysis, and finance study. To represent the data more efficiently, the mining process is supported by time series segmentation. Time series segmentation algorithm looks for the change points between two different patterns and develops a suitable model, depending on the data observed in such segment. Based on the issue of limited computing and storage capability, it is necessary to consider an adaptive and incremental online segmentation method. In this study, we propose an Online Empirical Bayesian Kernel Segmentation (OBKS), which combines …

Cybersecurity: Probabilistic Behavior Of Vulnerability And Life Cycle, Sasith Maduranga Rajasooriya

USF Tampa Graduate Theses and Dissertations

Analysis on Vulnerabilities and Vulnerability Life Cycle is at the core of Cybersecurity related studies. Vulnerability Life Cycle discussed by S. Frei and studies by several other scholars have noted the importance of this approach. Application of Statistical Methodologies in Cybersecurity related studies call for a greater deal of new information. Using currently available data from National Vulnerability Database this study develops and presents a set of useful Statistical tools to be applied in Cybersecurity related decision making processes.

In the present study, the concept of Vulnerability Space is defined as a probability space. Relevant theoretical analyses are conducted and …

Cybersecurity: Stochastic Analysis And Modelling Of Vulnerabilities To Determine The Network Security And Attackers Behavior, Pubudu Kalpani Kaluarachchi

USF Tampa Graduate Theses and Dissertations

Development of Cybersecurity processes and strategies should take two main approaches. One is to develop an efficient and effective set of methodologies to identify software vulnerabilities and patch them before being exploited. Second is to develop a set of methodologies to predict the behavior of attackers and execute defending techniques based on attacking behavior. Managing of Vulnerabilities and analyzing them is directly related to the first approach. Developing of methodologies and models to predict the behavior of attackers is related to the second approach. Both these approaches are inseparably interconnected. Our effort in this study mainly focuses on developing useful …

Analysis Of A Potential A(H7n9) Influenza Pandemic Outbreak In The U.S., Walter A. Silva Sotillo

USF Tampa Graduate Theses and Dissertations

This dissertation presents a collection of manuscripts that describe development of models and model implementation to analyze impact of potential A(H7N9) pandemic influenza outbreak in the U.S. Though this virus is still only animal-to-human transmittable, it has potential to become human-to-human transmittable and trigger a pandemic. This work is motivated by the negative impact on human lives that this virus has already caused in China, and is intended to support public health officials in preparing to protect U.S. population from a potential outbreak of pandemic scale.

An agent-based (AB) simulation model is used to replicate the social dynamics of the …

Real-Time Classification Of Biomedical Signals, Parkinson’S Analytical Model, Abolfazl Saghafi

USF Tampa Graduate Theses and Dissertations

The reach of technological innovation continues to grow, changing all industries as it evolves. In healthcare, technology is increasingly playing a role in almost all processes, from patient registration to data monitoring, from lab tests to self-care tools. The increase in the amount and diversity of generated clinical data requires development of new technologies and procedures capable of integrating and analyzing the BIG generated information as well as providing support in their interpretation.

To that extent, this dissertation focuses on the analysis and processing of biomedical signals, specifically brain and heart signals, using advanced machine learning techniques. That is, the …

Geospatial And Negative Binomial Regression Analysis Of Culex Nigripalpus, Culex Erraticus, Coquillettidia Perturbans, And Aedes Vexans Counts And Precipitation And Land Use Land Cover Covariates In Polk County, Florida, Joshua P. Wright

USF Tampa Graduate Theses and Dissertations

Although mosquito monitoring systems in the form of dry-ice bated CDC light traps and sentinel chickens are used by mosquito control personnel in Polk County, Florida, the placement of these are random and do not necessarily reflect prevalent areas of vector mosquito populations. This can result in significant health, economic, and social impacts during disease outbreaks. Of these vector mosquitoes Culex nigripalpus, Culex erraticus, Coquillettidia perturbans, and Aedes vexans are present in Polk County and known to transmit multiple diseases, posing a public health concern. This study seeks to evaluate the effect of Land use Land cover …

Robustness Of The Within- And Between-Series Estimators To Non-Normal Multiple-Baseline Studies: A Monte Carlo Study, Seang-Hwane Joo

USF Tampa Graduate Theses and Dissertations

In single-case research, multiple-baseline (MB) design is the most widely used design in practical settings. It provides the opportunity to estimate the treatment effect based on not only within-series comparisons of treatment phase to baseline phase observations, but also time-specific between-series comparisons of observations from those that have started treatment to those that are still in the baseline. In MB studies, the average treatment effect and the variation of these effects across multiple participants can be estimated using various statistical modeling methods. Recently, two types of statistical modeling methods were proposed for analyzing MB studies: a) within-series model and b) …

Modeling In Finance And Insurance With Levy-It'o Driven Dynamic Processes Under Semi Markov-Type Switching Regimes And Time Domains, Patrick Armand Assonken Tonfack

USF Tampa Graduate Theses and Dissertations

Mathematical and statistical modeling have been at the forefront of many significant advances in many disciplines in both the academic and industry sectors. From behavioral sciences to hard core quantum mechanics in physics, mathematical modeling has made a compelling argument for its usefulness and its necessity in advancing the current state of knowledge in the 21rst century. In Finance and Insurance in particular, stochastic modeling has proven to be an effective approach in accomplishing a vast array of tasks: risk management, leveraging of investments, prediction, hedging, pricing, insurance, and so on. However, the magnitude of the damage incurred in recent …

Applying Ahp And Clustering Approaches For Public Transportation Decisionmaking: A Case Study Of Isfahan City, Alireza Salavati, Hossein Haghshenas, Bahador Ghadirifaraz, Jamshid Laghaei, Ghodrat Eftekhari

Journal of Public Transportation

The main purpose of this paper is to define appropriate criteria for the systematic approach to evaluate and prioritize multiple candidate corridors for public transport investment simultaneously to serve travel demand, regarding supply of current public transportation system and road network conditions of Isfahan, Iran. To optimize resource allocation, policymakers need to identify proper corridors to implement a public transportation system. In fact, the main question is to adopt the best public transportation system for each main corridor of Isfahan. In this regard, 137 questionnaires were completed by experts, directors, and policymakers of Isfahan to identify goals and objectives in …

Efficiency Of An Unbalanced Design In Collecting Time To Event Data With Interval Censoring, Peiyao Cheng

USF Tampa Graduate Theses and Dissertations

In longitudinal studies, the exact timing of an event often cannot be observed, and is usually detected at a subsequent visit, which is called interval censoring. Spacing of the visits is important when designing study with interval censored data. In a typical longitudinal study, the spacing of visits is usually the same across all subjects (balanced design). In this dissertation, I propose an unbalanced design: subjects at baseline are divided into a high risk group and a low risk group based on a risk factor, and the subjects in the high risk group are followed more frequently than those in …

Hidden Markov Chain Analysis: Impact Of Misclassification On Effect Of Covariates In Disease Progression And Regression, Haritha Polisetti

USF Tampa Graduate Theses and Dissertations

Most of the chronic diseases have a well-known natural staging system through which the disease progression is interpreted. It is well established that the transition rates from one stage of disease to other stage can be modeled by multi state Markov models. But, it is also well known that the screening systems used to diagnose disease states may subject to error some times. In this study, a simulation study is conducted to illustrate the importance of addressing for misclassification in multi-state Markov models by evaluating and comparing the estimates for the disease progression Markov model with misclassification opposed to disease …

The Effects Of Age And Gender On Pedestrian Traffic Injuries: A Random Parameters And Latent Class Analysis, Tatok Raharjo Raharjo

USF Tampa Graduate Theses and Dissertations

Pedestrians are vulnerable road users because they do not have any protection while they walk. They are unlike cyclists and motorcyclists who often have at least helmet protection and sometimes additional body protection (in the case of motorcyclists with body-armored jackets and pants). In the US, pedestrian fatalities are increasing and becoming an ever larger proportion of overall roadway fatalities (NHTSA, 2016), thus underscoring the need to study factors that influence pedestrian-injury severity and potentially develop appropriate countermeasures. One of the critical elements in the study of pedestrian-injury severities is to understand how injuries vary across age and gender ‒ …

Statistical Analysis And Modeling Health Data: A Longitudinal Study, Bhikhari Prasad Tharu

USF Tampa Graduate Theses and Dissertations

Lung cancer has been considered one of the leading causes of deaths while cancer re- mains the second most common cause of deaths in the USA. Understanding the behavior of a disease over time could yield important information to make decisions about the disease. Statistical models could provide crucial clues and help to make a decision about the dis- ease, budget allocation, evaluation, and implement prevention. Longitudinal trend analysis of the diseases helps to understand long term effects and nature. Cholesterol level is one of the most contributing risk factors for Coronary Heart Disease. Studying cholesterol statistically helps to know …

Statistical Modeling Of Carbon Dioxide And Cluster Analysis Of Time Dependent Information: Lag Target Time Series Clustering, Multi-Factor Time Series Clustering, And Multi-Level Time Series Clustering, Doo Young Kim

USF Tampa Graduate Theses and Dissertations

The current study consists of three major parts. Statistical modeling, the connection between statistical modeling and cluster analysis, and proposing new methods to cluster time dependent information.

First, we perform a statistical modeling of the Carbon Dioxide (CO₂) emission in South Korea in order to identify the attributable variables including interaction effects. One of the hot issues in the earth in 21st century is Global warming which is caused by the marriage between atmospheric temperature and CO₂ in the atmosphere. When we confront this global problem, we first need to verify what causes the problem then we …

Time Dependent Kernel Density Estimation: A New Parameter Estimation Algorithm, Applications In Time Series Classification And Clustering, Xing Wang

USF Tampa Graduate Theses and Dissertations

The Time Dependent Kernel Density Estimation (TDKDE) developed by Harvey & Oryshchenko (2012) is a kernel density estimation adjusted by the Exponentially Weighted Moving Average (EWMA) weighting scheme. The Maximum Likelihood Estimation (MLE) procedure for estimating the parameters proposed by Harvey & Oryshchenko (2012) is easy to apply but has two inherent problems. In this study, we evaluate the performances of the probability density estimation in terms of the uniformity of Probability Integral Transforms (PITs) on various kernel functions combined with different preset numbers. Furthermore, we develop a new estimation algorithm which can be conducted using Artificial Neural Networks to …

A Statistical Analysis Of Hurricanes In The Atlantic Basin And Sinkholes In Florida, Joy Marie D'Andrea

USF Tampa Graduate Theses and Dissertations

Beaches can provide a natural barrier between the ocean and inland communities, ecosystems, and resources. These environments can move and change in response to winds, waves, and currents. When a hurricane occurs, these changes can be rather large and possibly catastrophic. The high waves and storm surge act together to erode beaches and inundate low-lying lands, putting inland communities at risk. There are thousands of buoys in the Atlantic Basin that record and update data to help predict climate conditions in the state of Florida. The data that was compiled and used into a larger data set came from two …

Modeling And Survival Analysis Of Breast Cancer: A Statistical, Artificial Neural Network, And Decision Tree Approach, Venkateswara Rao Mudunuru

USF Tampa Graduate Theses and Dissertations

Survival analysis today is widely implemented in the fields of medical and biological sciences, social sciences, econometrics, and engineering. The basic principle behind the survival analysis implies to a statistical approach designed to take into account the amount of time utilized for a study period, or the study of time between entry into observation and a subsequent event. The event of interest pertains to death and the analysis consists of following the subject until death. Events or outcomes are defined by a transition from one discrete state to another at an instantaneous moment in time. In the recent years, research …

Production Of Biodiesel From Soybean Oil Using Supercritical Methanol, Shriyash Rajendra Deshpande

USF Tampa Graduate Theses and Dissertations

The slow yet steady expansion of the global economies, has led to an increased demand for energy and fuel, which would eventually lead to shortage of fossil fuel resources in the near future. Consequently, researchers have been investigating other fuels like biodiesel. Biodiesel refers to the monoalkyl esters which can be derived from a wide range of sources like vegetable oils, animal fats, algae lipids and waste greases. Currently, biodiesel is largely produced by the conventional route, using an acid, a base or an enzyme catalyst. Drawbacks associated with this route result in higher production costs and longer processing times. …

Counter Machines And Crystallographic Structures, Natasha Jonoska, Mile Krajcevski, Gregory Mccolm

Mathematics and Statistics Faculty Publications

One way to depict a crystallographic structure is by a periodic (di)graph, i.e., a graph whose group of automorphisms has a translational subgroup of finite index acting freely on the structure. We establish a relationship between periodic graphs representing crystallographic structures and an infinite hierarchy of intersection languages DCL_d,d=0,1,2,…, within the intersection classes of deterministic context-free languages. We introduce a class of counter machines that accept these languages, where the machines with d counters recognize the class DCL_d. An intersection of d languages in DCL₁ defines DCL_d. We prove that there is …

Ehugs: Enhanced Hierarchical Unbiased Graph Shrinkage For Efficient Groupwise Registration, Guorong Wu, Xuewei Peng, Shihui Ying, Qian Wang, Pew-Thian Yap, Dan Shen, Dinggang Shen

Mathematics and Statistics Faculty Publications

Effective and efficient spatial normalization of a large population of brain images is critical for many clinical and research studies, but it is technically very challenging. A commonly used approach is to choose a certain image as the template and then align all other images in the population to this template by applying pairwise registration. To avoid the potential bias induced by the inappropriate template selection, groupwise registration methods have been proposed to simultaneously register all images to a latent common space. However, current groupwise registration methods do not make full use of image distribution information for more accurate registration. …

Open Access!: Review Of Online Statistics: An Interactive Multimedia Course Of Study By David Lane, Samuel L. Tunstall

Numeracy

David M. Lane (project leader). Online Statistics Education: An Interactive Multimedia Course of Study (http://onlinestatbook.com/)
Also: David M. Lane (primary author and editor), with David Scott, Mikki Hebl, Rudy Guerra, Dan Osherson, and Heidi Zimmer. Introduction to Statistics. Online edition (http://onlinestatbook.com/Online_Statistics_Education.pdf), 694 pp.

It is rare that students receive high-quality textbooks for free, but David Lane's Online Statistics: An Interactive Multimedia Course of Study permits precisely that. This review gives an overview of the many features in Lane's online textbook, including the Java Applets, the textbook itself, and the resources available for instructors. A discussion …

Infographics As Eye Candy: Review Of World War Ii In Numbers: An Infographic Guide To The Conflict, Its Conduct, And Its Casualties By Peter Doyle (2013), Joel Best

Numeracy

Peter Doyle. World War II in Numbers: An Infographic Guide to the Conflict, Its Conduct, and Its Casualties, illustrated by Lindsey Johns (Buffalo NY: Firefly Books, 2013). 224 pp. ISBN: 177085195X.

Doyle’s book contains dozens of graphs of statistical data dealing with World War II. Many of these graphs are visually striking. However, they often violate fundamental graphing principles, in that they distort quantitative relationships, use unidentified scales, and often make it difficult to compare quantities. Graphic software makes it easy to create imaginative images, but these can fail to communicate the very information that is the graph’s purpose.

Analysis Of Rheumatoid Arthritis Data Using Logistic Regression And Penalized Approach, Wei Chen

USF Tampa Graduate Theses and Dissertations

In this paper, a rheumatoid arthritis (RA) medicine clinical dataset with an ordinal response is selected to study this new medicine. In the dataset, there are four features, sex, age,treatment, and preliminary. Sex is a binary categorical variable with 1 indicates male, and 0 indicates female. Age is the numerical age of the patients. And treatment is a binary categorical variable with 1 indicates has RA, and 0 indicates does not have RA. And preliminary is a five class categorical variable indicates the patient’s RA severity status before taking the medication. The response Y is 5 class ordinal variable shows …

Ensemble Learning Method On Machine Maintenance Data, Xiaochuang Zhao

USF Tampa Graduate Theses and Dissertations

In the industry, a lot of companies are facing the explosion of big data. With this much information stored, companies want to make sense of the data and use it to help them for better decision making, especially for future prediction. A lot of money can be saved and huge revenue can be generated with the power of big data. When building statistical learning models for prediction, companies in the industry are aiming to build models with efficiency and high accuracy. After the learning models have been developed for production, new data will be generated. With the updated data, the …