根據金管會銀行局的統計資料顯示，台灣在2005年2月底信用卡流通卡數已高逹44,611仟張，是1992年底信用卡流通卡數的近30倍。雖然信用卡流通卡數持續增長，在1992年底時成長率高逹62.1%，之後在這十年間信用卡流通卡數成長率幾乎都有30%以上的成長率，1996年成長率為48.7%，此時正為產品生命周期中的成長期。觀察近二年信用卡流通卡數的成長率，2004年只有16.7%，今年(2005年)成長率卻下滑到1%左右，可見信用卡市場已從生命周期中的成長期逐漸邁向成熟期。銀行若想在競爭激烈的信用卡市場中搶得先機，進而獲取利潤，應進行所謂產品的製程創新，即如何在信用卡進入產品生命周期的成熟期中，加強信用風險控管以降低成本、提高消費性產品即信用卡的品質和附加價值，以及如何進一步鞏固現有的信用卡客戶。本研究擬將提供一個具體之模型，以供日後銀行預測信用卡持卡人違約或剪卡之用。 本論文擬使用國內某家銀行在2004年3月底於資料倉儲中的客戶資料，有效分析客戶數共計128萬多筆。首先，本文先將信用卡客戶依人口統計變數、信用卡持卡人與發卡機構往來狀況、信用卡持卡人之使用狀況、信用卡持卡人之消費行為以及信用卡客戶付款狀況，探討信用卡客戶的剪卡概況。接著建構一個logistic model來預測客戶的剪卡機率，再用quantile regression model 分別對高剪卡率及低剪卡率之信用卡客戶進行分析。本文的重要發現有： 1. 年齡、是否使用循環利息在不同分量下，對於剪卡率的影響皆為負向關係，而且隨著分量愈大，剪卡率下降的幅度也愈多。 2. 每月限額、半年內交易次數、預借現金次數在不同分量下，對於剪卡率的影響皆為負向關係，而且隨著分量愈大，剪卡率下降的幅也愈少。 3. 婚姻狀況、有效信用卡數在不同分量下，對於剪卡率的影響皆為正向關係，而且隨著分量愈大，剪卡率增加的幅度也愈大。 銀行可根據重要的發現結果來制定授信政策，例如在每月限額部份，對於高剪卡率的客戶而言，若提高此客戶的信用額度，將使其剪卡率下降幅度少於低剪卡率的客戶，因此，銀行可著重在鞏固低剪卡率的客戶，藉由調高其信用額度，增加這群客戶對銀行信用卡的品牌忠誠度。或者可加以參考客戶的其它持卡消費行為，使授信政策更為完全，而且又可以滿足現存客戶的需求。

Source: Dissertation Abstracts International, Volume: 70-03, Section: B, page: 1743. Advisers: Wenyaw Chan; Glasser H. Jay. Includes bibliographical references.

Context: When a software is modified, regression testing is performed to ensure the behaviour of software is not affected because of those modifications. Due to frequent modifications, the regression testing became challenging. Although there are many regression testing techniques are developed in the research, they are not incorporating in the industry. This is because of the differences in regression testing goals and measures in research and industry. The current context of this study is to identify the regression testing goals and measures in the research and industry perspectives and to find the differences and similarities in both perspectives. Objectives: The primary objective of this study is to identify the similarities and differences in regression testing goals and measure from research and industry perspectives. Additionally, in this study, a general adapted goals list is presented. Methods: A mixed method approach is used for this study. A literature review has been used to identify the regression testing goals and measures in research. A survey is used to identify the regression testing goals and measures in the industry. Semi-structured interviews and online questionnaire are used as data collection methods in the survey. Thematic analysis and descriptive statistics are used as data analysis methods for the qualitative and quantitative data. Results: A literature review is conducted using 33 research articles. In the survey, the data is collected from 11 semi-structured interviews which are validated with 45 responses from an online questionnaire. A total of 6 regression testing goals are identified from the literature review and 8 goals are identified in the survey respectively. The measures used to evaluate these goals are identified and tabulated. Conclusions: From the results, we observed the similarities and differences in the regression testing goals and measures in industry and research. There are few similarities in goals but the major difference is the priority order of these goals. There are various measures used in research but very fewer measures are incorporating in the industry. The respondents from the survey implied that there is a need for generic adaptive goals. Further, a general list of goals is presented. Keywords: Regression, Regression testing, Goals, Objectives, Measures, Metrics.

Master of Science / Department of Statistics / Trevor Hefley / Binary regression models for spatial data are commonly used in disciplines such as epidemiology and ecology. Many spatially-referenced binary data sets suffer from location error, which occurs when the recorded location of an observation differs from its true location. When location error occurs, values of the covariates associated with the true spatial locations of the observations cannot be obtained. We show how a change of support (COS) can be applied to regression models for binary data to provide bias-corrected coefficient estimates when the true values of the covariates are unavailable, but the unknown location of the observations are contained within non-overlapping polygons of any geometry. The COS accommodates spatial and non-spatial covariates and preserves the convenient interpretation of methods such as logistic and probit regression. Using a simulation experiment, we compare binary regression models with a COS to naive approaches that ignore location error. We illustrate the flexibility of the COS by modeling individual-level disease risk in a population using a binary data set where the location of the observations are unknown, but contained within administrative units. Our simulation experiment and data illustration corroborate that conventional regression models for binary data which ignore location error are unreliable, but that the COS can be used to eliminate bias while preserving model choice.

Varying diameter ratios associated with smooth concentric tube-in-tube heat exchangers are known to have an effect on its convective heat transfer capabilities. Much literature exists for predicting the inner tube’s heat transfer coefficients, however, limited research has been conducted for the annulus and some of the existing correlations are known to have large errors. Linear and nonlinear regression models exist for determining the heat transfer coefficients, however, these are complex and time consuming methods and require much experimental data in order to obtain accurate solutions. A direct solution to obtain the heat transfer coefficients in the annulus is sought after. In this study a large dataset of experimental measurements on heat exchangers with annular diameter ratios of 0.483, 0.579, 0.593 and 0.712 was gathered. The annular diameter ratio is defined as the ratio of the outer diameter of the inner tube to the inner diameter of the outer tube. Using various methods, the data was processed to determine local and average Nusselt numbers in the turbulent flow regime. These methods included the modified Wilson plot technique, a nonlinear regression scheme, as well as the log mean temperature difference method. The inner tube Reynolds number exponent was assumed to be a constant 0.8 for both the modified Wilson plot and nonlinear regression methods. The logarithmic mean temperature difference method was used for both a mean analysis on the full length of the heat exchanger, and a local analysis on finite control volumes. Friction factors were calculated directly from measured pressure drops across the annuli. The heat exchangers were tested for both a heated and cooled annulus, and arranged in a horizontal counter-flow configuration with water as the working medium. Data was gathered for Reynolds numbers (based on the hydraulic diameter) varying from 10 000 to 28 000 for a heated annulus and 10 000 to 45 000 for a cooled annulus. Local inner wall temperatures which are generally difficult to determine, were measured with thermocouples embedded within the wall. Flow obstructions within the annuli were minimized, with only the support structures maintaining concentricity of the inner and outer tubes impeding flow. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Mechanical and Aeronautical Engineering / unrestricted

A Monte Carlo simulation was used to generate data for a comparison of five robust regression estimation methods with ordinary least squares (OLS) under 36 different outlier data configurations. Two of the robust estimators, Least Absolute Value (LAV) estimation and MM estimation, are commercially available. Three authormodified variations on MM were also included (MM1, MM2, and MM3). Design parameters that were varied include sample size (n=60 and n=180), number of independent predictor variables (2, 3 and 6), outlier density (0%, 5% and 15%) and outlier location (2x,2y s, 8x8y s, 4x,8y s and 8x,4y s). Criteria on which the regression methods were measured are relative efficiency, bias and a test of the null hypothesis. Results indicated that MM2 was the best performing robust estimator on relative efficiency. The best performing estimator on bias was MM1. The best performing regression method on the test of the null hypothesis was MM2. Overall, the MM-type robust regression methods outperformed OLS and LAV on relative efficiency, bias, and the test of the null hypothesis.

Philosophiae Doctor - PhD / One of the assumptions of conventional regression analysis is I that the parameters are constant over all observations. It has often been suggested that this may not be a valid assumption to make, particularly if the econometric model is to be used for economic forecasting0 Apart from this it is also found that econometric models, in particular, are used to investigate the underlying interrelationships of the system under consideration in order to understand and to explain relevant phenomena in structural analysis. The pre-requisite of such use of econometrics is that the regression parameters of the model is assumed to be constant over time or across different crosssectional units.

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The global sustainable development has been marked by the United Nations plans for more than two decades. These plans have been adopted by most of the developed and developing countries to achieve the 2030 Agenda, currently formed by the 17 Sustainable Development Goals. Governments and policy-makers cannot make conscious decisions regarding sustainability progress without knowledge about how well the country is performing this path. This study assessed the evolution of each SDG in Spain through their indicators and whether correlation and dependency between the stated targets exist. Goals 1, 2, 6, 8 and 11 were the less evolved, those which were undergoing a slower process or a negative evolution over the years. The correlation analysis delivered a quick guide of relationships amidst targets to help the appropriate ministries to make prompt decisions knowing which fields will be affected largely. Goal 3 (Good health and well-being) was strongly linked with indicators from Goal 4 (Quality education) and also Goal 6 (Clean water and sanitation). Furthermore, indicators from Goal 7 (Affordable and clean energy) shared a high correlation with the ones from Goal 12 (Responsible consumption and production) and Goal 15 (Life on land). All together obtained 60% share of positive interactions and almost 80% of significant interplays between the targets. Correlation does not imply causality, so multiple linear regression analysis set true numerical relationships and revealed how to enhance certain targets by leveraging others. Less developed indicator was taken as dependent variables and the final independent ones were defined using shrinkage methods. The procedure to reach these expressions could be used to establish the dependency between other relevant indicators and getting the assessment of the performance of this country afterwards. / Den globala hållbara utvecklingen har präglats av FN:s planer i mer än två decennier. Dessa planer har antagits av de flesta av de utvecklade länderna och utvecklingsländerna för att uppnå agenda 2030, som för närvarande bildas av de 17 globala målen för hållbar utveckling (SDG). Regeringar och beslutsfattare kan inte fatta medvetna beslut om hållbarhetsframsteg utan kunskap om hur väl landet presterar denna väg. Denna studie undersökte utvecklingen av varje SDG i Spanien genom deras indikatorer och huruvida korrelation och beroende finns mellan de angivna målen. Mål 1, 2, 6, 8 och 11 var de mindre utvecklade. De genomgick en långsammare process eller hade negativ utveckling under åren. Korrelationsanalysen levererade en snabb guide över relationer förhållandet bland mål för att hjälpa de berörda ministerierna att fatta snabba beslut om att veta vilka områden som i hög grad kommer att påverkas. Mål 3 (God hälsa och välbefinnande) var starkt kopplat till indikatorer från mål 4 (Kvalitetsutbildning) och även mål 6 (Rent vatten och sanitet). Dessutom hade indikatorer från mål 7 (prisvärd och ren energi) en hög korrelation med indikatorer från mål 12 (Ansvarsfull konsumtion och produktion) och mål 15 (Liv på land). Tillsammans erhöll 60% positiva interaktioner och nästan 80% betydande samspel mellan målen. Korrelation innebär inte orsakssamband, så flera linjära regressionsanalyser satte riktiga numeriska förhållanden och avslöjade hur man kan förbättra vissa mål genom att utnyttja andra. Mindre utvecklade indikatorer togs som beroende variabler och de slutliga oberoende variablerna definierades med krympningsmetoder. Tillvägagångssättet för att nå dessa uttryck kan användas för att fastställa beroendet mellan andra relevanta indikatorer och få en utvärdering av landets resultat.

It is estimated that one third of the world's population is infected with tuberculosis. Though once thought a "dead" disease, tuberculosis is very much alive. The rise of drug resistant strains of tuberculosis, and TB-HIV coinfection have made tuberculosis an even greater worldwide threat. While HIV, poverty, and public health infrastructure are historically assumed to affect the burden of tuberculosis, recent research has been done to implicate smoking in this list. This analysis involves combining data from multiple sources in order determine if smoking is a statistically significant factor in predicting the number of incident tuberculosis cases in a country. Quasi-Poisson generalized linear models and negative binomial regression will be used to analyze the effect of smoking, as well as the other factors, on tuberculosis incidence. This work will enhance tuberculosis control efforts by helping to identify new hypotheses that can be tested in future studies. One of the main hypotheses is whether or not smoking increases the number of tuberculosis cases above and beyond the effects of other factors that are known to influence tuberculosis incidence. These known factors include TB-HIV coinfection, poverty and public health infrastructure represented by treatment outcomes.