Physical Sciences and Mathematics Commons^™

Statistical Analysis And Mechanistic Modeling Of Water Quality: Hillsborough Bay, Florida, Keith Hackett

USF Tampa Graduate Theses and Dissertations

Nutrient pollution has been identified as a significant threat to U.S. coastal and estuarine water quality. Though coastal and estuarine waters need nutrients to maintain a healthy, productive ecosystem, excess nutrients can lead to eutrophication. There are significant potential negative consequences associated with eutrophication, including loss of habitat, loss of economic activity, and direct threats to human health. Hillsborough Bay experienced eutrophication in the 1960s and 1970s due to a rapidly growing population and associated increases in nutrient pollution. These eutrophic conditions led to more frequent phytoplankton and macroalgae blooms and declines in seagrasses. To address these problems, a series …

Parametric And Bayesian Modeling Of Reliability And Survival Analysis, Carlos A. Molinares

USF Tampa Graduate Theses and Dissertations

The objective of this study is to compare Bayesian and parametric approaches to determine the best for estimating reliability in complex systems. Determining reliability is particularly important in business and medical contexts. As expected, the Bayesian method showed the best results in assessing the reliability of systems.

In the first study, the Bayesian reliability function under the Higgins-Tsokos loss function using Jeffreys as its prior performs similarly as when the Bayesian reliability function is based on the squared-error loss. In addition, the Higgins-Tsokos loss function was found to be as robust as the squared-error loss function and slightly more efficient. …

Estimating Statistical Characteristics Under Interval Uncertainty And Constraints: Mean, Variance, Covariance, And Correlation, Ali Jalal-Kamali

Open Access Theses & Dissertations

In many practical situations, we have a sample of objects of a given type. When we measure the values of a certain quantity x for these objects, we get a sequence of values x1, . . . , xn. When the sample is large enough, then the arithmetic mean E of the values xi is a good approximation for the average value of this quantity for all the objects from this class. Other expressions provide a good approximation to statistical characteristics such as variance, covariance, and correlation.

The values xi come from measurements, and measurement is never absolutely accurate.

Often, …

Summative Confidence, Paul Cristian Gugiu

Dissertations

Often the singular goal of an evaluation is to render a summative conclusion of merit, worth or feasibility that is based on multiple streams of multidimensional data. Exacerbating this difficulty, conducting evaluations in real-world settings often necessitates implementation of less than ideal study designs. This reality gets further complicated by the standard method for estimating the precision of results via the confidence interval (CI). Traditional CIs offer a limited approach for understanding the precision of a summative conclusion. This dissertation develops and presents a unified approach for the construction of a CI for a summative conclusion (SC).

This study derived …

Robust Adaptive Scheme For Linear Mixed Models, Gabriel Asare Okyere

Dissertations

If the underlying distribution of a statistical model is known then a procedure which maximizes power and efficiency can be selected. For example, if the distribution of errors is known to be normal in a linear model then inference based on least squares maximizes power and efficiency. More generally, if this distribution is known then a ranked based inference based on the appropriate rank score function has maximum efficiency. In practice, though, this distribution is not known. Adaptive schemes are procedures which hopefully select appropriate methods to optimize the analysis.

Hogg (1974) presented an adaptive rank-based scheme for testing in …

Robust Nonparametric Methods For Regression To The Mean Model, Therawat Wisadrattanapong

Dissertations

Regression to the mean is a statistical phenomenon that often confounds treatment effects in experiments. Consider an experiment involving a treatment, in which a response is measured (baseline) on a subject then a treatment is applied and a second measurement is taken. Then under many bivariate models for the pair of responses (including the bivariate normal), the predicted response of the second measurement will regress to the mean. In experiments where the second response is only taken for a select sample, say above a cutoff value, then this regression to the mean effect may mistakenly be thought of as a …

An Analog Experiment Comparing Goal-Free Evaluation And Goal Achievement Evaluation Utility, Brandon W. Youker

Dissertations

Goal-free evaluation (GFE) is the process of determining the merit of an evaluand independent of the stated or implied goals and objectives, whereas goal achievement evaluation (GAE), as the most rudimentary form of goal-based evaluation, determines merit according to the evaluand’s level of accomplishment with regard to its goals. This study examines the utility of GAE and GFE from the perspective of the evaluation’s intended users. In the study, two evaluation teams, goal achievement and goal-free, independently and simultaneously evaluate the same human service program. Each team produced a final evaluation report, which was read by the evaluation’s users, who …

Estimating The Effect Of Dust And Low Wind Events On Hospitalizations For Asthma While Adjusting For Hourly Levels Of Air Pollutants, Priyangi Kanchana Bulathsinhala

Open Access Theses & Dissertations

El Paso, Texas is known as one of the dust hotspots in North America. We explore the effect of dust and low wind events on asthma admissions in El Paso, Texas between 2000 and 2005. Conditional logistic regression with a case-crossover design was used to estimate the probability of hospitalization after dust and low wind events while controlling for pollutants with hourly monitor measurements, and weather. The historical functional linear model is used to incorporate the hourly pollutant measures into the regression model with a continuous lag, as an alternative to a distributed lag model based on daily averages. The …

Modeling And Analysis Of Repeated Ordinal Data Using Copula Based Likelihoods And Estimating Equation Methods, Raghavendra Rao Kurada

Mathematics & Statistics Theses & Dissertations

Repeated or longitudinal ordinal data occur in many fields such as biology, epidemiology, and finance. These data normally are analyzed using both likelihood and non-likelihood methods. The first part of this dissertation discusses the multivariate ordered probit model which is a likelihood method based on latent variables. We show that this latent variable model belong to a very general class of Copula models. We use the copula representation for the multivariate ordered probit model to obtain maximum likelihood estimates of the parameters. We apply the methodology in the analysis of real life data examples.

Though likelihood methods are preferable, there …

The Doubly Inflated Poisson And Related Regression Models, Manasi Sheth-Chandra

Mathematics & Statistics Theses & Dissertations

Most real life count data consists of some values that are more frequent than allowed by the common parametric families of distributions. For data consisting of only excess zeros, in a seminal paper Lambert (1992) introduced Zero-Inflated Poisson (ZIP) model, which is a mixture model that accounts for the inflated zeros. In this thesis, two Doubly Inflated Poisson (DIP) probability models, DIP (p, λ) and DIP ( p1, p2, λ), are discussed for situations where there is another inflated value k > 0 besides the inflated zeros. The distributional properties such as identifiability, moments, and conditional probabilities …