Thesis (Ph. D.)--University of Wisconsin--Madison, 1969. / Typescript. Vita. Includes bibliographical references (leaves [184]-190) and abstract.

Thesis (Ph. D.)--University of Chicago, Dept. of Statistics, December 2002. / Includes bibliographical references. Also available on the Internet.

Thesis (M.S.)--Boise State University, 2009. / Title from t.p. of PDF file (viewed May 5, 2010). Includes abstract. Includes bibliographical references (leaf 21).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1967. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliography.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006. / Huo, Xiaoming, Committee Member ; Heil, Chris, Committee Member ; Wang, Yang, Committee Member ; Hayter, Anthony, Committee Member ; Vidakovic, Brani, Committee Chair.

Thesis (Ph.D.)--University of Toledo, 2005. / Typescript. "A dissertation [submitted] as partial fulfillment of the requirements of the Doctor of Philosophy degree in Mathematics." Bibliography: leaves 100-105.

Thesis (Ph. D.)--University of Texas at Dallas, 2006. / Includes vita. Includes bibliographical references (leaves 92-93).

Capturing CO2 produced by power plants and storing it within depleted oil and natural gas reservoirs in the seabed offers a potential means to reduce the emissions that contribute to climate change. This is known as carbon capture and storage (CCS). CO2 captured from power plants is transported to these reservoirs using pipelines. To determine the parameters of pipeline operation this calls for a need to characterise, via an "equation of state", the physical properties of CO2 during transport. Doing so is further complicated by the fact that CO2 captured from power stations is typically a mixture of CO2 with other fluids. This affects the physical properties of the CO2 to be transported and so needs to be accounted for. In this thesis we develop statistical models for equations of state that can account for the physical properties of CO2 relevant to carbon capture and storage, and which allow us to quantify uncertainty in the predictions from the equation of state. We propose two statistical models for equations of state. Firstly we develop a statistical model which can be applied to any pressure-explicit parametric equation of state. To do so we have developed a novel method by which to rigorously account for uncertainties due to coexistence which is complicated by the fact that it involves perfectly correlated measurements on two fluid phases. We fit this model to pure CO2 obtaining good agreement with data for most temperatures. We then extended this model and our method for accounting for coexistence to mixtures. We fit this model to real CO2-H2 data. Despite mixing well, the results of this fit do not agree well with the data and equations of state need to be developed further to be able to model mixture data well. Secondly we develop a non-parametric Gaussian process approach which offers greater flexibility and requires fewer assumptions. This non-parametric model is fit to pure CO2 reference data for individual subcritical temperatures. We demonstrate how applying a transformation to the covariance function can account for non-stationarity in the data resulting in good agreement between predictions from the fit model and the data.

According to the National Water Act of 1998, an estuary is an enclosed body of water that is either periodically or permanently open to the ocean. Within an estuary, the seawater is diluted to a measurable degree, creating a unique aquatic environment for animals and plants. Estuaries are environmental and economic assets to the population. The health status of our local estuaries, however, is being compromized due to a steady decrease in the freshwater inflow and supply. Tides and climatic conditions do have an impact upon the dynamics of an estuary, but these factors remain relatively constant throughout each year. The freshwater inflow and supply, however, are highly variable and are directly influenced by human involvement. Upstream abstraction for industrial and domestic use, for example, could lead to mouth closure where the ocean meets the river. The National Water Act of 1998 was established to address the lack of research and predominant mismanagement of freshwater inflow into South Africa’s estuaries (Allanson and Baird, 1999). To ensure proper water resource management, different water allocation costs and benefits need to be compared and analyzed to secure an optimum solution (Mlangeni, 2007). Like many environmental services yielded to man, estuary services are not traded in any markets. Alternative markets are thus sought to allow the estimation of the values of such services. Among the available valuation techniques are the Contingent Valuation Method (CVM), Travel Cost Method (TCM) and Hedonic Pricing Method (HPM). The involved benefits of water allocations are predicted in this study by use of the CVM which elicits respondents’ willingness to pay (WTP) towards predetermined changes in freshwater inflow into estuaries. The CVM was applied throughout the Water Research Commission’s (WRC) Project K5/1413 from 2000 to 2008 (Hosking, 2010). Each individual study employed specialized surveys which ideally created a close correspondence between the answers provided by respondents to the supposed scenarios and their voluntary exchanges in markets should money actually have been handled (Mlangeni, 2007). Much criticism has been directed towards the CVM, but careful use and application of the method has been shown to produce significant and satisfactory results (Hosking, 2010). The primary aim of this study was to collectively analyze the collated data provided by the WRC and compare the results with the findings of previous studies. Each variable was analyzed separately in order to reveal any discrepancies between the respective findings. A supplementary objective of this study was to add to the body of knowledge pertaining to South Africa’s estuaries and guide management in the distribution of freshwater towards proficient levels (Du Preez and Hosking, 2010). The associated change in the cumulative consumer surplus with an increased freshwater supply into forty selected estuaries was therefore investigated. The subsequent benefits due to a superior freshwater supply are therefore reflected (Du Preez and Hosking, 2010). The data gathered by each of the individual researchers throughout their studies (supported by the WRC) were combined to form a single dataset including all recorded information supplied by the corresponding respondents. As the investigation progressed, improvements were made upon the questionnaires posed to the considered estuary populations. Consequently, some of the data in the combined dataset were “missing”, since previous studies did not include certain questions, while later studies omitted others. Data imputation was employed to create an imputed dataset, enabling the modeling of the public’s WTP through regression techniques. A linear model was utilized in this study, also incorporating interaction between the predictor variables. The double-log functional form was implemented to estimate the public’s WTP. The population’s total willingness to pay (TWTP) was further estimated by aggregation. A summary of the respective results is displayed in in Table 1.

The roots of a plant play a vital role in its growth and development, but due to practical difficulties of observing underground roots, the study of their shape has long been neglected. Recent advances in CT imaging technology have allowed for accurate non-destructive imaging of root systems in soil. This technique has formed the basis of the FutureRoots project. The main challenge with analysing the shape of a plant root system is that they have varying topological structure, so traditional shape analysis methods cannot be applied. In this thesis, we develop three approaches for analysing wheat root systems. The first approach involves measuring a set of pre-chosen root traits, and analysing this set using conventional statistical methods. This approach is effective but may miss potentially important shape information and the large number of measurable traits reduces the potential power of statistical tests. The second approach is to perform pairwise comparisons based on the Hausdorff Metric and use Multidimensional scaling to reduce a large set of pairwise comparisons to a dataset which can be analysed with conventional statistical methods. This approach can detect and test for overall shape differences but can fail to detect subtle differences. The third approach is to apply the Persistent Homology technique from Topological Data Analysis, which is designed to find underlying topological differences between two shapes. This method successfully finds differences but it is difficult to interpret the results. We will apply these three techniques to simulated data and a real life dataset. In addition, because of experimental considerations, the wheat roots had to be unnaturally constrained to a small area so we have developed a method to estimate how they would have grown unconstrained.