The use of statistics has been common practice within the petroleum industry for over a decade. With such a mature subject that includes specialized software and numerous articles, the challenge of this project was to introduce a duplicable method to perform deterministic regression while confirming the mathematical and actual validation of the resulting model. A five-step procedure was introduced using Statistical Analysis Software (SAS) for necessary computations to obtain a model that describes an event by analyzing the environmental variables. Since SAS may not be readily available, the code to perform the five-step methodology in R has been provided. The deterministic five-step procedure methodology may be applied to new fields with a limited amount of data. As an example case, 17 wells drilled in north central Texas were used to illustrate how to apply the methodology to obtain a deterministic model. The objective was to predict the number of days required to drill a well using environmental conditions and technical variables. Ideally, the predicted number of days would be within +/- 10% of the observed time of the drilled wells. The database created contained 58 observations from 17 wells with the descriptive variables, technical limit (referred to as estimated days), depth, bottomhole temperature (BHT), inclination (inc), mud weight (MW), fracture pressure (FP), pore pressure (PP), and the average, maximum, and minimum difference between fracture pressure minus mud weight and mud weight minus pore pressure. Step 1 created a database. Step 2 performed initial statistical regression on the original dataset. Step 3 ensured that the models were valid by performing univariate analysis. Step 4 history matched the models-response to actual observed data. Step 5 repeated the procedure until the best model had been found. Four main regression techniques were used: stepwise regression, forward selection, backward elimination, and least squares regression. Using these four regression techniques and best engineering judgment, a model was found that improved time prediction accuracy, but did not constantly result in values that were +/- 10% of the observed times. The five-step methodology to determine a model using deterministic statistics has applications in many different areas within the petroleum field. Unlike examples found in literature, emphasis has been given to the validation of the model by analysis of the model error. By focusing on the five-step procedure, the methodology may be applied within different software programs, allowing for greater usage. These two key parameters allow companies to obtain their time prediction models without the need to outsource the work and test the certainty of any chosen model.

This thesis describes the application of a novel decision support process for machined part estimating in small and medium-sized engineering companies. Many SMEs tend to adopt manual estimating techniques, however this dependence on human expertise represents a risk to such organizations. Better information management in estimating can improve process performance and contribute to increased competitiveness. The research which is the subject of this thesis investigated whether a systems approach to machined part estimating would extend the capacity of an SME to manage knowledge more effectively. The research explored the workplace learning context, the provision of learning opportunities and the management of organizational knowledge; before determining that an intelligent information system offered the most beneficial solution to the situation-of-interest. The case study company produce low-volume, make-to-order, medium and large sized machined steel forgings; utilising conventional machine tool equipment. The application of the decision support system enabled novice estimators to produce viable cost estimates; reducing the risk from reliance on human expertise inherent in manual estimating. The hybrid feature-based costing / case-based reasoning estimating technique, which is the core of the novel METALmpe cost model, proved exceptionally well suited to the SME environment. Estimates produced using METALmpe were consistently more accurate than those of the human expert; with a level of accuracy that exceeds the initial research aim, i.e. a tolerance of -5% / +10%. Significantly, implementation of METALmpe (hardware, software and support for 5 users), can be provided at a cost which is within the typical information technology budget of many SMEs. With demands on organizations to process and disseminate ever increasing volumes of information, METALmpe can improve an SME’s information management capabilities and contribute to competitive advantage through strengthening strategic assets and core competencies.

The research was conducted in the light of a training programme which will train a total of 150 engineers of AVIC I in Cranfield University during a period of 3 years. Cost has become an essential driver to aircraft design, as well as performances due to either the limited defence budget or competitive airline market. Consequently, knowing the possible cost prior to making actual expenditure will help managers to make proper decisions and allocate resources efficiently, and designers to optimize their work. Existing aircraft cost estimating models are outdated and mainly based on a database including both military and civil aircraft with various missions. This research concentrated on commercial jet aircraft and was to develop a suitable acquisition cost estimating methodology for conceptual design from a commercial aircraft manufacturer’s perspective. The literature reviewing took a comprehensive overview of some widely-applied cost estimating methods: Analogy, Parametric, Bottom-up, Feature-based costing, Activitybased costing (ABC), Expert judgement, and etc. Some practical cost models were also reviewed to learn the application of cost estimating in the aerospace industry. Then, analogy and parametric approaches were selected to perform the methodology development considering the limited data available at the conceptual design phase. An investigation was deployed to identify the actual problems in practice. The results helped to recognize the needs of industry. Also, the preparation works for development are presented to understand the environment. With subjective judgement and statistical techniques, a series of cost estimating relationships (CERs) were achieved, in which some historic explanatory parameters remained or were eliminated, and some new ones introduced. Size of aircraft became another variable besides weight. As to engines, all developed explanatory variables have been revealed in prior researches. The validation of CERs proves that they can provide reliable cost estimates with high accuracy and can be applied to conceptual design. In addition, a case study was conducted using a baseline aircraft defined in the group design project (GDP) and presents cost forecasting for the proposed aircraft. At last, discussion and conclusion presents an overview of the research. A framework for cost estimating system can be educed. Also, the future work is proposed for in-depth research.

No description available.

Generalized estimating equations (GEEs) are commonly used in the modelling of correlated data. However, in the presence of informative cluster sizes, estimates obtained using GEEs may be biased. In order to correct for this bias a weighted GEE may be used. Previous research has extended the use of weighted GEEs to a longitudinal setting but requires that cluster sizes remain constant over time. In this thesis, two new weighting schemes are investigated to allow for valid parameter estimation in a longitudinal setting where cluster sizes are informative and may change over time. Specifically, this thesis considers weighting by the inverse of the time-dependent cluster size, and by the total number of observations for a given cluster. Through Monte Carlo simulation, the performance of traditional GEEs, GEEs under previously proposed weighting schemes, and these two new models are compared. Results of these studies show that weighting by the total number of observations results in unbiased parameter estimates with excellent coverage.

The empirical likelihood method introduced by Owen (1988, 1990) is a powerful nonparametric method for statistical inference. It has been one of the most researched methods in statistics in the last twenty-five years and remains to be a very active area of research today. There is now a large body of literature on empirical likelihood method which covers its applications in many areas of statistics (Owen, 2001). One important problem affecting the empirical likelihood method is its poor accuracy, especially for small sample and/or high-dimension applications. The poor accuracy can be alleviated by using high-order empirical likelihood methods such as the Bartlett corrected empirical likelihood but it cannot be completely resolved by high-order asymptotic methods alone. Since the work of Tsao (2004), the impact of the convex hull constraint in the formulation of the empirical likelihood on the finite sample accuracy has been better understood, and methods have been developed to break this constraint in order to improve the accuracy. Three important methods along this direction are [1] the penalized empirical likelihood of Bartolucci (2007) and Lahiri and Mukhopadhyay (2012), [2] the adjusted empirical likelihood by Chen, Variyath and Abraham (2008), Emerson and Owen (2009), Liu and Chen (2010) and Chen and Huang (2012), and [3] the extended empirical likelihood of Tsao (2013) and Tsao and Wu (2013). The latter is particularly attractive in that it retains not only the asymptotic properties of the original empirical likelihood, but also its important geometric characteristics. In this thesis, we generalize the extended empirical likelihood of Tsao and Wu (2013) to handle inferences in two large classes of one-sample and two-sample problems. In Chapter 2, we generalize the extended empirical likelihood to handle inference for the large class of parameters defined by one-sample estimating equations, which includes the mean as a special case. In Chapters 3 and 4, we generalize the extended empirical likelihood to handle two-sample problems; in Chapter 3, we study the extended empirical likelihood for the difference between two p-dimensional means; in Chapter 4, we consider the extended empirical likelihood for the difference between two p-dimensional parameters defined by estimating equations. In all cases, we give both the first- and second-order extended empirical likelihood methods and compare these methods with existing methods. Technically, the two-sample mean problem in Chapter 3 is a special case of the general two-sample problem in Chapter 4. We single out the mean case to form Chapter 3 not only because it is a standalone published work, but also because it naturally leads up to the more difficult two-sample estimating equations problem in Chapter 4. We note that Chapter 2 is the published paper Tsao and Wu (2014); Chapter 3 is the published paper Wu and Tsao (2014). To comply with the University of Victoria policy regarding the use of published work for thesis and in accordance with copyright agreements between authors and journal publishers, details of these published work are acknowledged at the beginning of these chapters. Chapter 4 is another joint paper Tsao and Wu (2015) which has been submitted for publication. / Graduate / 0463 / fwu@uvic.ca

This thesis aimed to apply the causal framework with potential outcomes to examine the causal effect of air temperature on reported violent crimes in Swedish municipalities. The Generalized Estimating Equations method was used on yearly, monthly and also July only data for the time period 2002-2014. One significant causal effect was established but the majority of the results pointed to there being no causal effect between air temperature and reported violent crimes.

Project (M.U.A.)--Virginia Polytechnic Institute and State University, 1991. / Includes bibliographical references (leaf 27). Also available via the Internet.

Thesis (M.Phil.) - University of St Andrews, January 2008.

Thesis (M.S.)--University of Wisconsin, 1959. / Extension Repository Collection. Typescript (carbon copy). Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 88-90).