Statistical Methodology Commons^™

A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo

FIU Electronic Theses and Dissertations

Traffic simulation software is used by transportation researchers and engineers to design and evaluate changes to roadway networks. Underlying these simulators are mathematical models of microscopic driver behavior from which macroscopic measures of flow and congestion can be recovered. Many models are intended to apply to only a subset of possible traffic scenarios and roadway configurations, while others do not have any explicit constraint on their applicability. Work zones on highways are one scenario for which no model invented to date has been shown to accurately reproduce realistic driving behavior. This makes it difficult to optimize for safety and other …

Examining The Effects Of Individual And Neighborhood Factors On Hiv Transmission Risk Potential Among People With Hiv, Semiu Olatunde Gbadamosi

FIU Electronic Theses and Dissertations

HIV transmission risk significantly increases in late-diagnosed HIV and at HIV viral load (VL) >1500 copies/mL. The objective of this dissertation was to examine factors associated with HIV transmission risk potential for persons with HIV (PWH) using measures of time from HIV infection to diagnosis and trajectories of VL suppression. Additionally, we sought to determine whether a single yearly VL measure—the current standard to track the HIV epidemic in the United States—is reliable in assessing viral suppression for PWH. The first study estimated the distribution of time from HIV infection to diagnosis in Florida using a CD4 depletion model and …

Best Probable Subset: A New Method For Reducing Data Dimensionality In Linear Regression, Elieser Nodarse

FIU Electronic Theses and Dissertations

Regression is a statistical technique for modeling the relationship between a dependent variable Y and two or more predictor variables, also known as regressors. In the broad field of regression, there exists a special case in which the relationship between the dependent variable and the regressor(s) is linear. This is known as linear regression.

The purpose of this paper is to create a useful method that effectively selects a subset of regressors when dealing with high dimensional data and/or collinearity in linear regression. As the name depicts it, high dimensional data occurs when the number of predictor variables is far …

Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral

FIU Electronic Theses and Dissertations

The increasing volume of information has created overwhelming challenges to extract the relevant items manually. Fortunately, the online systems, such as e-commerce (e.g., Amazon), location-based social networks (LBSNs) (e.g., Facebook) among many others have the ability to track end users' browsing and consumption experiences. Such explicit experiences (e.g., ratings) and many implicit contexts (e.g., social, spatial, temporal, and categorical) are useful in preference elicitation and recommendation. As an emerging branch of information filtering, the recommendation systems are already popular in many domains, such as movies (e.g., YouTube), music (e.g., Pandora), and Point-of-Interest (POI) (e.g., Yelp).

The POI domain has many …

Sabermetrics - Statistical Modeling Of Run Creation And Prevention In Baseball, Parker Chernoff

FIU Electronic Theses and Dissertations

The focus of this thesis was to investigate which baseball metrics are most conducive to run creation and prevention. Stepwise regression and Liu estimation were used to formulate two models for the dependent variables and also used for cross validation. Finally, the predicted values were fed into the Pythagorean Expectation formula to predict a team’s most important goal: winning.

Each model fit strongly and collinearity amongst offensive predictors was considered using variance inflation factors. Hits, walks, and home runs allowed, infield putouts, errors, defense-independent earned run average ratio, defensive efficiency ratio, saves, runners left on base, shutouts, and walks per …

On Some Ridge Regression Estimators For Logistic Regression Models, Ulyana P. Williams

FIU Electronic Theses and Dissertations

The purpose of this research is to investigate the performance of some ridge regression estimators for the logistic regression model in the presence of moderate to high correlation among the explanatory variables. As a performance criterion, we use the mean square error (MSE), the mean absolute percentage error (MAPE), the magnitude of bias, and the percentage of times the ridge regression estimator produces a higher MSE than the maximum likelihood estimator. A Monto Carlo simulation study has been executed to compare the performance of the ridge regression estimators under different experimental conditions. The degree of correlation, sample size, number of …

On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar

FIU Electronic Theses and Dissertations

Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo …

A Comparison Of Some Confidence Intervals For Estimating The Kurtosis Parameter, Guensley Jerome

FIU Electronic Theses and Dissertations

Several methods have been proposed to estimate the kurtosis of a distribution. The three common estimators are: g₂, G₂ and b₂. This thesis addressed the performance of these estimators by comparing them under the same simulation environments and conditions. The performance of these estimators are compared through confidence intervals by determining the average width and probabilities of capturing the kurtosis parameter of a distribution. We considered and compared classical and non-parametric methods in constructing these intervals. Classical method assumes normality to construct the confidence intervals while the non-parametric methods rely on bootstrap techniques. The bootstrap …

On Some Test Statistics For Testing The Population Skewness And Kurtosis: An Empirical Study, Yawen Guo

FIU Electronic Theses and Dissertations

The purpose of this thesis is to propose some test statistics for testing the skewness and kurtosis parameters of a distribution, not limited to a normal distribution. Since a theoretical comparison is not possible, a simulation study has been conducted to compare the performance of the test statistics. We have compared both parametric methods (classical method with normality assumption) and non-parametric methods (bootstrap in Bias Corrected Standard Method, Efron’s Percentile Method, Hall’s Percentile Method and Bias Corrected Percentile Method). Our simulation results for testing the skewness parameter indicate that the power of the tests differs significantly across sample sizes, the …

Power Comparison Of Some Goodness-Of-Fit Tests, Tianyi Liu

FIU Electronic Theses and Dissertations

There are some existing commonly used goodness-of-fit tests, such as the Kolmogorov-Smirnov test, the Cramer-Von Mises test, and the Anderson-Darling test. In addition, a new goodness-of-fit test named G test was proposed by Chen and Ye (2009). The purpose of this thesis is to compare the performance of some goodness-of-fit tests by comparing their power.

A goodness-of-fit test is usually used when judging whether or not the underlying population distribution differs from a specific distribution. This research focus on testing whether the underlying population distribution is an exponential distribution.

To conduct statistical simulation, SAS/IML is used in this research. Some …

Combined Computational-Experimental Design Of High-Temperature, High-Intensity Permanent Magnetic Alloys With Minimal Addition Of Rare-Earth Elements, Rajesh Jha

FIU Electronic Theses and Dissertations

AlNiCo magnets are known for high-temperature stability and superior corrosion resistance and have been widely used for various applications. Reported magnetic energy density ((BH) _max) for these magnets is around 10 MGOe. Theoretical calculations show that ((BH) _max) of 20 MGOe is achievable which will be helpful in covering the gap between AlNiCo and Rare-Earth Elements (REE) based magnets. An extended family of AlNiCo alloys was studied in this dissertation that consists of eight elements, and hence it is important to determine composition-property relationship between each of the alloying elements and their influence on the bulk properties.

In …

Gis-Integrated Mathematical Modeling Of Social Phenomena At Macro- And Micro- Levels—A Multivariate Geographically-Weighted Regression Model For Identifying Locations Vulnerable To Hosting Terrorist Safe-Houses: France As Case Study, Elyktra Eisman

FIU Electronic Theses and Dissertations

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to …