This study investigates the linkage between long-run and short-run dynamics of exchange rate determination for the German mark/U.S. dollar quarterly rate for the period 1973-1990. Earlier investigations failed to explicitly take into account the possible nonstationarity of the data set they were using. This study continues the work performed in this area by applying modern econometric techniques to empirical tests of the Dornbusch model. In essence, this study revives the monetary model and determines if the empirical analysis using the German/U.S. case derives elements which are compatible with the monetary theory of exchange rate determination.

In this dissertation, we apply Bayesian and Empirical Bayes methods for reliability growth models based on the power law process. We also apply Bayes methods for the study of microarrays, in particular, in the selection of differentially expressed genes. The power law process has been used extensively in reliability growth models. Chapter 1 reviews some basic concepts in reliability growth models. Chapter 2 shows classical inferences on the power law process. We also assess the goodness of fit of a power law process for a reliability growth model. In chapter 3 we develop Bayesian procedures for the power law process with failure truncated data, using non-informative priors for the scale and location parameters. In addition to obtaining the posterior density of parameters of the power law process, prediction inferences for the expected number of failures in some time interval and the probability of future failure times are also discussed. The prediction results for the software reliability model are illustrated. We compare our result with the result of Bar-Lev,S.K. et al. Also, posterior densities of several parametric functions are given. Chapter 4 provides Empirical Bayes for the power law process with natural conjugate priors and nonparametric priors. For the natural conjugate priors, two-hyperparameter prior and a more generalized three-hyperparameter prior are used. In chapter 5, we review some basic statistical procedures that are involved in microarray analysis. We will also present and compare several transformation and normalization methods for probe level data. The objective of chapter 6 is to select differentially expressed genes from tens of thousands of genes. Both classical methods (fold change, T-test, Wilcoxon Rank-sum Test, SAM and local Z-score and Empirical Bayes methods (EBarrays and LIMMA) are applied to obtain the results. Outputs of a typical classical method and a typical Empirical Bayes Method are discussed in detail.

Validity generalization work over the past 25 years has called into question the veracity of the assumption that validity is situationally specific. Recent theoretical and methodological work has suggested that validity coefficients may be transportable even if true validity is not a constant. Most transportability work is based on the assumption that the distribution of rho ( ρi ) is normal, yet, no empirical evidence exists to support this assumption. The present study used a competing model approach in which a new procedure for assessing transportability was compared with two more commonly used methods. Empirical Bayes estimation (Brannick, 2001; Brannick & Hall, 2003) was evaluated alongside both the Schmidt-Hunter multiplicative model (Hunter & Schmidt, 1990) and a corrected Hedges-Vevea (see Hall & Brannick, 2002; Hedges & Vevea, 1998) model. The purpose of the present study was two-fold. The first part of the study compared the accuracy of estimates of the mean, standard deviation, and the lower bound of 90 and 99 percent credibility intervals computed from the three different methods across 32 simulated conditions. The mean, variance, and shape of the distribution varied across the simulated conditions. The second part of the study involved comparing results of analyses of the three methods based on previously published validity coefficients. The second part of the study was used to show whether choice of method for determining whether transportability is warranted matters in practice. Results of the simulation analyses suggest that the Schmidt-Hunter method is superior to the other methods even when the distribution of true validity parameters violates the assumption of normality. Results of analyses conducted on real data show trends consistent with those evident in the analyses of the simulated data. Conclusions regarding transportability, however, did not change as a function of method used for any of the real data sets. Limitations of the present study as well as recommendations for practice and future research are provided.

Information security technologists and business scholars are motivated by a desire to understand how and to what extent the application of IT within enterprise systems leads to improved and secured organizational performance. An effective relationship between business and IT professionals is a primary determinant of success in gaining business advantage through the enterprise system. As business innovation has relied increasingly on partnerships between business and IT professional, a different perspective of how IT professionals view their organizational contributions was needed for organizations to remain competitive. Business knowledge is essential if IT professionals are to create linkages with other organizational units and have a wider perspective about business objectives, thus achieving fit between IT and organizational strategies. Organizations have started responding to this challenge by demanding more business acumen in their IT staff. The focus of this study is on the knowledge that is beyond that of independent business and IT only domain knowledge of information security. Therefore, technical areas of knowledge, such as hardware and software, all of which are closely associated with IT skills, are not discussed in this thesis. This is not to declare that such knowledge is not important. Clearly technical knowledge is part of the IT professional's overall information security technology expertise, but this study is about the organization proficiency of business and the IT professional, and is therefore interested in what enables business and IT professionals to apply their business domain and technical knowledge in ways that are beneficial to the organization and to act cooperatively with their customers and business partners. The purpose of this study is to employ the triangulation method to identify the theoretical links and empirically examine the association between business and IT perspective of information security. An important contribution of this study is the identification of business and IT perspectives on information security technology. By establishing the link between business and IT, the study focuses and evaluates Virtual Private Network (VPN) as an information security technology to find out if VPN can secure and gain competitive advantage by partisan business process and organization performance. This study articulates distinctive characteristics of Virtual Private Network and management processes that extend the range of applicability across diverse business segments. It distinguishes between business and IT and explains why the exploitation of a complementary set of related information security entities (such as VPN) across multiple functions create competitive vi advantages even across a diverse set of businesses that have limited opportunity to exploit business process and organization performance. The most important direct predictor of this study is a high level of communication between business and IT. However, one cannot mandate meaningful communication between individuals. IT people have to earn the right to play a meaningful role in management forums. Based on the findings from this study, one important way for an IT person to be heard is for him/her to devote the time necessary to create competitive advantage and develop shared domain knowledge, the most influential construct in the research model. An IT person needs to understand the leverage points of the industry, the history and current issues of the business units, and to learn to apply business oriented objectives in the application of technology to business problems. This change in view would help focus their attention on security technology and ideas that could produce the most benefit and create competitive advantage, rather than those that offer the most technical promise.

There is a renewed interest in further exploring the significance of culture to the accounting disclosure model in view of a highly competitive global business environment. To date, there is no empirical research to investigate this issue with respect to a specific industry, namely banking. There are three main reasons for focusing only on the banking industry (Hooi 2004). First, it is considered to be the most important industry for the country’s economic and financial stability. Moreover, the IASB has recognised its significance by issuing unique accounting standards i.e. IAS30, IAS32 and IAS39. Second, Saidenberg and Schuermann (2003) argue that with the scope and complexity of Basel II, it provides opportunities for researching issues through Pillar 3. Third, with national banking systems being non-homogenous, it is important to investigate the effects of national culture because prior research has argued that cultural differences have partly explained international differences in disclosure framework of accounting systems. The purpose of this study is to apply and extend Gray’s (1988) theoretical framework of national culture with respect to four research questions. First, to contribute to Gray’s (1988) theory of cultural influence on international banking disclosures. Second, to investigate the possible significance of investor protection to the banking disclosure model. Third, to explore Gray’s (1988) theory on the relationship of national culture to capital market research using banking returns. Fourth, to investigate the value relevance of investor protection and banking disclosures to the returns model. Seventeen developed and developing countries with a representative sample of 37 listed domestic commercial banks were examined in 2004. For the disclosure model, the study finds that national culture is a significant factor in the banking industry. Individualism has been found as the primary cultural dimension for banking disclosures. Moreover, the explanatory power of the model significantly improves with the legal dimensions of common law and anti-director rights. The positive association between common law and banking disclosures is consistent with La Porta et al. (1998) which argue that common law countries with stronger investor protection are more transparent than civil law countries. However, there is a negative association between investor protection variable of anti-director rights with banking disclosures. This may suggest that investor protection does not encourage minority investors to enter the stock market specifically in the global banking industry. This situation may lead to a lack of demand for transparency through a smaller dispersion of ownership across the domestic banks. For the returns model, the study finds that national culture is value relevant in the banking industry. Collectivism and power distance have been found to be the two primary cultural dimensions for banking returns. Moreover, the explanatory power of the model significantly improves with anti-director rights and banking disclosures. These results are (1) consistent with La Porta et al. (2002) which argue that investor protection increases firm valuation with respect to Tobin’s Q and (2) international investors tend to support the Basel Committee’s commitment in providing a more transparent framework by implementing Pillar 3 in the near future, starting with the Basel member countries. Finally, an interesting finding from the study is that firm size has a negative association with banking returns.

The relative power of goodness-of-fit test statistics has long been debated in the literature. Chi-Square type test statistics to determine 'fit' for categorical data are still dominant in the goodness-of-fit arena. Empirical Distribution Function type goodness-of-fit test statistics are known to be relatively more powerful than Chi-Square type test statistics for restricted types of null and alternative distributions. In many practical applications researchers who use a standard Chi-Square type goodness-of-fit test statistic ignore the rank of ordinal classes. This thesis reviews literature in the goodness-of-fit field, with major emphasis on categorical goodness-of-fit tests. The continued use of an asymptotic distribution to approximate the exact distribution of categorical goodness-of-fit test statistics is discouraged. It is unlikely that an asymptotic distribution will produce a more accurate estimation of the exact distribution of a goodness-of-fit test statistic than a Monte Carlo approximation with a large number of simulations. Due to their relatively higher powers for restricted types of null and alternative distributions, several authors recommend the use of Empirical Distribution Function test statistics over nominal goodness-of-fit test statistics such as Pearson's Chi-Square. In-depth power studies confirm the views of other authors that categorical Empirical Distribution Function type test statistics do not have higher power for some common null and alternative distributions. Because of this, it is not sensible to make a conclusive recommendation to always use an Empirical Distribution Function type test statistic instead of a nominal goodness-of-fit test statistic. Traditionally the recommendation to determine 'fit' for multivariate categorical data is to treat categories as nominal, an approach which precludes any gain in power which may accrue from a ranking, should one or more variables be ordinal. The presence of multiple criteria through multivariate data may result in partially ordered categories, some of which have equal ranking. This thesis proposes a modification to the currently available Kolmogorov-Smirnov test statistics for ordinal and nominal categorical data to account for situations of partially ordered categories. The new test statistic, called the Combined Kolmogorov-Smirnov, is relatively more powerful than Pearson's Chi-Square and the nominal Kolmogorov-Smirnov test statistic for some null and alternative distributions. A recommendation is made to use the new test statistic with higher power in situations where some benefit can be achieved by incorporating an Empirical Distribution Function approach, but the data lack a complete natural ordering of categories. The new and established categorical goodness-of-fit test statistics are demonstrated in the analysis of categorical data with brief applications as diverse as familiarity of defence programs, the number of recruits produced by the Merlin bird, a demographic problem, and DNA profiling of genotypes. The results from these applications confirm the recommendations associated with specific goodness-of-fit test statistics throughout this thesis.

Algorithms that learn sets of rules describing a concept from its examples have been widely studied in machine learning and have been applied to problems in medicine, molecular biology, planning and linguistics. Many of these algorithms used a separate-and-conquer strategy, repeatedly searching for rules that explain different parts of the example set. When examples are scarce, however, it is difficult for these algorithms to evaluate the relative quality of two or more rules which fit the examples equally well. This dissertation proposes, implements and examines a general technique for modifying rule evaluation in order to improve learning performance in these situations. This approach, called Description-based Evaluation Function Transfer (DEFT), adjusts the way rules are evaluated on a target concept by taking into account the performance of similar rules on a related support task that is supplied by a domain expert. Central to this approach is a novel theory of task similarity that is defined in terms of syntactic properties of rules, called descriptions, which define what it means for rules to be similar. Each description is associated with a prior distribution over classification probabilities derived from the support examples and a rule's evaluation on a target task is combined with the relevant prior using Bayes' rule. Given some natural conditions regarding the similarity of the target and support task, it is shown that modifying rule evaluation in this way is guaranteed to improve estimates of the true classification probabilities. Algorithms to efficiently implement Deft are described, analysed and used to measure the effect these improvements have on the quality of induced theories. Empirical studies of this implementation were carried out on two artificial and two real-world domains. The results show that the inductive transfer of evaluation bias based on rule similarity is an effective and practical way to improve learning when training examples are limited.

在台灣證券市場中，有許多的技術分析方法或指標，市場參與者或財 務學者會利用歷史資料來做回溯測試，找出可運用的方法或指標，以此來 推測出台股加權指數未來的趨勢，也有學者利用類神經網路(Artificial Neural Network, ANN)考慮經濟景氣、技術分析指標等作為輸入變數來預測 台股加權指數，而本文則利用 EEMD(Ensemble Empirical Mode Decomposition)拆解出來的結果作為 ANN 的輸入變數，並將 ANN 預測出 的值轉換成 FK (Forward-calculated %K) 值，再搭配不同的交易方式，來 補捉台股加權指數的走勢，並比較各種交易方式的績效，找出一個能夠穩 定獲利的交易模型。

The Dissertation sets out the results of an evaluation of certain aspects of the Commonwealth of Australia's Freedom of Information Legislation and proposals to introduce a Freedom of Information Law in Sri Lanka. The major purpose of the study was: (i) to evaluate whether the Commonwealth FOI Act has achieved the objects of Parliament - whether members of the public could have a free access to government information subject to important exemptions. (ii) whether a FOI regime should be introduced to Sri Lanka In conducting my research, I devoted three chapters to FOI in Australia including the development of the legislation. I analysed key components of the legislation and researched to what extent the FOI Act has achieved its objects. I devoted two chapters towards the concept of transparency of government in Sri Lanka, the attitude of the Courts towards the concept of the right to information and whether Sri Lanka needs a Freedom of Information Act. In the last two chapters, I have devoted a chapter each to the concept of translocation of laws and about an ideal FOI Act for Sri Lanka, which is an adaptation of the Australian Act. The individual components of the methodology incorporated: (i) a literature survey of the Commonwealth FOI Act, Freedom of Information in the United Nations and in the USA; and Sweden, Canada and New Zealand; (ii) a literature survey concerning the transparency of government in Sri Lanka (ii) interviews with a cross section Commonwealth FOI administrators and key politicians, lawyers and a cross section of members of the press and public in Sri Lanka; and (iv) research of the Australian FOI legislation The empirical data present an analysis of key features of the Commonwealth FOI Act with particular attention to exemption clauses. I have recommended some amendments to the FOI Act in view of the Commonwealth Government's policy of outsourcing some of its activities and the creation of a position of FOI Commissioner. Finally my research indicates that Sri Lanka needs Freedom of Information legislation to meet the challenges facing a developing country that is endeavoring to reach 'newly developed status' early in the new millennium. Furthermore, international lenders and donors are now requiring that developing countries like Sri Lanka seeking aid, should show more transparency in its activities. I have drafted a Freedom of Jiformation Bill for Sri Lanka. I have based the draft on the Australian law adapted to suit the local conditions in Sri Lanka, which is in Appendix "G".

We present limit theory for tests of homogeneity for finite mixture models. More specifically, we derive the asymptotic distribution of certain random quantities used for testing that a mixture of two distributions is in fact just a single distribution. Our methods apply to cases where the mixture component distributions come from one of a wide class of one-parameter exponential families, both continous and discrete. We consider two random quantities, one related to testing simple hypotheses, the other composite hypotheses. For simple hypotheses we consider the maximum of the standardised score process, which is itself a test statistic. For composite hypotheses we consider the maximum of the efficient score process, which is itself not a statistic (it depends on the unknown true distribution) but is asymptotically equivalent to certain common test statistics in a certain sense. We show that we can approximate both quantities with the maximum of a certain Gaussian process depending on the sample size and the true distribution of the observations, which when suitably normalised has a limiting distribution of the Gumbel extreme value type. Although the limit theory is not practically useful for computing approximate p-values, we use Monte-Carlo simulations to show that another method suggested by the theory, involving using a Studentised version of the maximum-score statistic and simulating a Gaussian process to compute approximate p-values, is remarkably accurate and uses a fraction of the computing resources that a straight Monte-Carlo approximation would.