傳統迴歸分析是假設觀測值的不確定性來自於隨機現象，本文則應用模糊隨機變數概念於迴歸模式的架構，考慮將隨機現象和模糊認知並列研究。針對樣本模糊數(x_i, Y_i)，我們進行模糊迴歸參數估計，並稱此為模糊迴歸模式分析。模糊迴歸參數估計大都採用線性規劃，求出適當區間，將觀測模糊數Y_i的分佈範圍全部覆蓋。但是此結果並不能充分反映觀測樣本Y_i的特性。本研究提出一套模糊迴歸參數的估計方法，其結果對觀測樣本的解釋將更為合理，且具有模糊不偏的特性。在分析過程中，我們亦提出一些模糊統計量如模糊期望值、模糊變異數、模糊中位數的定義，以增加對這些參數的模糊理解。最後在本文中也針對台灣景氣指標與經濟成長率作實務分析，說明模糊迴歸模式的適用性。 / Conventional study on the regression analysis is based on the conception that the uncertainty of observed data comes from the random property. However, in this paper we consider both of the random property and the fuzzy perception to construct the regression model by using of fuzzy random variables. For the fuzzy sample (x_i,Y_i), we will process the parameters estimation of the fuzzy regression, and we call this process as fuzzy regression analysis. The parameters estimation for a fuzzy regression model is generally derived by the linear programming scheme. But it's result usually doesn't sufficiently reflect the characteristics of the observed samples. Hence in this paper we propose an alternative technique for parameters estimation in constructing the fuzzy regression model. The result will describe the observed data better than the conventional method did, moreover it will have the fuzzy unbiased properties. For the purpose of fuzzy perception on the fuzzy random variables, we also give definitions for certain important fuzzy statistics such as fuzzy expected value, fuzzy variance and fuzzy median. Finally, we give an example about the Taiwan Business Cycle and the Taiwan Economic Growth Rate for illustration.

房屋貸款保證保險制度可移轉部分違約風險予保險公司。然而，保險公司與金融機構在共同承擔風險之際，因房貸保證保險制度之施行，於提高貸款成數後，產生違約風險提高之矛盾現象；而估計保險之預期損失時，以目前尚無此制度下之違約數據估計損失額，將有錯估之可能。 本研究以二元邏吉斯特迴歸模型(Binary Logistic Regression Model)與存活分析(Survival Analysis)估計違約行為，並比較各模型間資料適合度及預測能力，進而單獨分析變數-貸款成數對違約率之邊際機率影響。以探討房貸保證保險施行後，因其對借款者信用增強而提高之貸款成數，所增加之違約風險。並評估金融機構因提高貸款成數後可能之違約風險變動，據以推估違約率數據，並根據房貸保證保險費率結構模型，計算可能之預期損失額，估算變動的保險費率。 實證結果發現，貸款成數與違約風險呈現顯著正相關，貸款成數增加，邊際影響呈遞增情形，違約率隨之遞增，而違約預期損失額亦同時上升。保險公司因預期損失額增加，為維持保費收入得以支付預期損失，其保險費率將明顯提升。故實施房屋貸款保證保險，因借款者信用增強而提高之貸款成數，將增加違約機率並對保險費率產生直接變動。 / Mortgage insurance system may transfer part of the default risk to insurance companies. However, the implementation of mortgage insurance system, on increasing loan to value ratio, the resulting increase default risk. And literatures estimate the expected loss without the default data, there will be misjudge. Our study constructs the binary logistic regression model and survival analysis to estimate the mortgage default behavior, and compare the data between the model fit and the predictive power. Analyzes the effect of loan to value ratio on the marginal probability of default rate. Furthermore, assess the financial institutions in the risk of default due to loan to value ratio changes. According to the estimated default rate data, we employ the mortgage insurance rate structural model to calculate the expected amount of loss and the changes in premium rates. Empirical results found loan to value ratio have a significant positive effect on borrowers’ default. Loan to value ratio increase, the marginal effect progressively increase, along with increasing default rates and expected default losses. Due to the ascendant expected loss, insurance companies increase premiums to cover the expected loss, the premium rate will be significantly improved. Therefore, the implementation of mortgage insurance, credit enhancement for the borrower to improve loan to value ratio, will increase the probability of default and insurance rates.

授信業務是銀行主要獲利來源之一，隨著國際化趨勢以及政府積極推動經濟自由，國內金融環境丕變，金融機構之授信業務競爭日漸激烈，加上近年來國內經濟成長趨緩，又於千禧年爆發本土性金融風暴，集團企業財務危機猶如骨牌效應ㄧ樁接ㄧ樁，原因在於大企業過度信用擴張，過高槓桿操作，導致負債比率上升，面臨償債困難；還有銀行對企業放款之授信審核常有大企業不會倒閉之迷思。故如何找出企業財務危機出現之徵兆，及早防範於未然，將是本研究在建立企業授信之申請進件模型的重點之ㄧ。 此外，2002年新修定的巴塞爾資本協定主在落實銀行風險管理，國際清算銀行決定於2006年正式實行新巴塞爾協定，我國修正的「銀行資本適足性管理辦法」自民國九十五年十二月三十一日起實施，故本國銀行需要依據本身的商品特色、市場區隔、客戶性質、以及經營方式與理念等因素，去建制一套適合自己的內部風險評估系統。故本研究第二個重點即在於依據我國現有法令，做出一個符合信用風險基礎內部評等法要求之申請進件模型。 本研究使用某銀行有財務報表之企業授信戶，利用財報中的財務比率變數建立模型。先使用主成分分析將所有變數分為七大類，分別是企業之財務構面、經營能力、獲利能力、償債能力、長期資本指標、流動性、以及現金流量，再進行羅吉斯迴歸模型分析。 / Business loan is one of the main profits in the bank. But increasing business competition causes the loan process in the bank is not very serious, the bankers allow enterprise to expand his credit or has higher debt ratio, that would cause financial crises. The first point in this study is to find the symptom when enterprise has financial crises. The second point is that under the framework of New Basel Capital Accord〈Basel II〉, we try to build an application model that committed the domestic requirements. The bank should develop the fundamental internal rating-based approach that accords with its strategy、market segmentation、and customers type. This research paper uses financial variables〈ex. liquid ratio、debt ratio、ROA、ROE、… 〉to build enterprise application model. We use the principle component analysis to separate different factors which affect loan process： financial facet、ability to pay、profitability、management ability、long-term index、liquidity、and cash flow. Then, we show the result about these factors in the logistic regression model.

不景氣的年代，民間企業裁員、減薪或強迫員工休無薪假的事件層出不窮，襯托出公職相對起薪高、福利制度健全，任職免職程序有政府法令保障。在公職逐漸被當前的社會氛圍視為是兼具地位及幸福的工作時，愈來愈多的民眾競相投入公務人員的考試，而競相爭捧鐵飯碗的現象，也成為近期媒體報導的新聞焦點。 惟前述種種的論述都仍停留在主觀的聯想及推論上，國內鮮少針對經濟變數與公務人員考試錄取率間之關係，建立統計實證模型進行客觀量化分析。基於這樣的時空背景及社會氛圍，本研究遂以客觀的高普考錄取率表示公務人員考試競爭程度，觀察經濟環境變數對其造成的影響，是否誠如媒體所言，當景氣愈差時，公職考試就愈熱門的現象。 經過實證模型分析後，發現影響經濟變數對高考錄取率較普考錄取率變動數的影響較為顯著，包括：當期或前期的高考薪資占民間薪資比、當期或前期的失業率、前期臺股指數變動數、當期或前期臺股指數標準離差率以及時間趨勢等解釋變數，並且各自存在不同程度的影響及合理的正負關係。而普考錄取率變動數部分，僅受當期普考薪資占民間薪資比、前期失業率及時間趨勢等變數所影響。 本文最後，提出針對可能影響民眾報考公務人員的重要因素，提出相應政策建議，以期抒緩公職考試過熱的現象並精進政府政策。 / Recession-era, layoffs, pay cuting, and forcing employees to take unpaid leave are more and more in private sector, highlight the work of public sector is high starting salary, benefits sound system, and having protection by law in appointment and dismissal. More people want to participate in civil service examination, then civil service examination craze has become the focus of recent news. Provided the foregoing various opinions are still subjective conjecture, almost no study about relationship between economic variables and the qualification rates of civil service examination in domestic studies. In this context, this study used a senior and junior civil service examination qualification rates to represent the competitive of civil service examination, and to observe the effects of economic variables on the qualification rates of civil service examination, if consistent with the media reports, the worse economy is, the less qualification rates of civil service examination will be. After empirical model analysis, we found that the effects of economic variables on the qualification rates of senior civil service examination are more significant than the changes of the qualification rates of junior civil service examination. Finally, make recommendations to relief civil service examination craze.

在可預見之未來無線點對點的世界裡，資訊交易就如同現實世界人與人間的交易模式，需考量到交易資訊的成本、價值與人際關係衡量之因素；傳統廣告行銷的效率問題也待創新的資訊交易平台來解決。本研究提出的資訊交易模型，以人性考量為基礎，在各種不同情境下，動態衡量資訊成本、價值與使用者間關係，透過助理軟體，協助加入資訊交易平台之個體，以更便利方式進行資訊交易，預期讓交易結果更貼近使用者的需求；而企業方面也能透過點與點之間快速傳遞資訊的特性，預期以更低成本、更高效率，完成商務行銷目的，達到破壞性行銷之目標。 / This paper presents a novel ambient e-service aiming at distributed marketing through sensible bartering in foreseeable wireless Peer-to-Peer (WP2P) environments. A variety of influential factors (e.g., cost, value, relationship) are proposed and formalized for empowering the bartering mechanism, unfolding a rich arena of ambient distributed trading and a disruptive paradigm of e-marketing.

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

Dans le chapitre 1, j’examine les résultats des fusions entre producteurs européens d’énergie en termes d’efficacité. Je calcule l’éco-efficacité en utilisant l’analyse de l’enveloppement des données et l’indice de productivité Malmquist-Luenberger. Je trouve que les fusions horizontales nationales, qui sont soigneusement réglementées, n’ont pas d’impact. Les fusions horizontales transfrontalières nuisent à l’éco-efficacité à court terme mais la stimulent deux ans après l’achèvement. Les fusions verticales nuisent à l’éco-efficacité. Je présente des suggestions de politiques concernant la réglementation des fusions. Le chapitre 2 est un travail conjoint avec Julian Hinz. Nous enquêtons sur les effets de l’embargo russe auto-imposé sur les importations de produits alimentaires en provenance des pays occidentaux. Nous construisons un modèle ricardien avec des liens sectoriels, des échanges de biens intermédiaires et une hétérogénéité sectorielle dans la production. L’étalonnage du modèle avec des données réelles permet de simuler les résultats de l’embargo en termes de changements de bien-être et de prix. Nous quantifions en outre l’impact sur les prix à la consommation en Russie à l’aide de la méthode des doubles différences. Le chapitre 3 est basé sur un article co-écrit avec Cristina Herghelegiu. Nous enquêtons sur l’utilisation des conditions commerciales internationales (Incoterms). Ce sont les schémas prédéfinis de la répartition des coûts et des risques entre les acheteurs et les vendeurs. Nous nous appuyons sur un ensemble de données très détaillées sur les exportations russes durant la période 2012-2015. Nous constatons que les grandes entreprises sont plus susceptibles d’assumer des responsabilités. Les gros acheteurs assument plus de responsabilités, quelle que soit la taille du vendeur, alors que les gros vendeurs le font uniquement lorsque leur partenaire est petit. C’est plus probable que les risques et les coûts sont sur les acheteurs dans les transactions de biens intermédiaires et de biens d’équipement. / In Chapter 1 I investigate firm-level efficiency outcomes of mergers between the European energy producers. I compute eco-efficiency using data envelopment analysis and the Malmquist-Luenberger productivity index. I find that carefully regulated domestic horizontal mergers do not have a statistically significant impact. Cross-border horizontal mergers hamper eco-efficiency in the short run but stimulate it two years after completion. Vertical mergers are detrimental to eco-efficiency. I put forward policy suggestions regarding the regulation of mergers. Chapter 2 is joint work with Julian Hinz. We investigate the effects of self-imposed Russian embargo on food import from Western countries. We build a Ricardian model with sectoral linkages, trade in intermediate goods and sectoral heterogeneity in production. The calibration of the model with real data allows to simulate the outcomes of embargo in terms of changes in welfare and prices. We further quantify the impact on consumer prices in Russia with the difference-in-differences estimator. Chapter 3 is based on a paper co-written with Cristina Herghelegiu. We investigate the use of International Commercial Terms. They are pre-defined schemes of repartition of costs and risks between buyers and sellers, which serve to mitigate the uncertainty. We rely on a highly detailed dataset on Russian exports over the 2012-2015 period. We find that big firms are more likely to take on responsibilities. Big buyers bear more responsibilities regardless of the seller size, whereas big sellers do so only when their partner is small. Risks and costs are more likely on buyers in transactions of intermediate and capital goods.

Propor uma família de distribuição de probabilidade mais ampla e flexível é de grande importância em estudos estatísticos. Neste trabalho é utilizado um novo método de adicionar um parâmetro para uma distribuição contínua. A distribuição gama generalizada, que tem como casos especiais a distribuição Weibull, exponencial, gama, qui-quadrado, é usada como distribuição base. O novo modelo obtido tem quatro parâmetros e é chamado odd log-logística gama generalizada (OLLGG). Uma das características interessante do modelo OLLGG é o fato de apresentar bimodalidade. Outra proposta deste trabalho é introduzir um modelo de regressão chamado log-odd log-logística gama generalizada (LOLLGG) com base na GG (Stacy e Mihram, 1965). Este modelo pode ser muito útil, quando por exemplo, os dados amostrados possuem uma mistura de duas populações estatísticas. Outra vantagem da distribuição OLLGG consiste na capacidade de apresentar várias formas para a função de risco, crescente, decrescente, na forma de U e bimodal entre outras. Desta forma, são apresentadas em ambos os casos as expressões explícitas para os momentos, função geradora e desvios médios. Considerando dados nãocensurados e censurados de forma aleatória, as estimativas para os parâmetros de interesse, foram obtidas via método da máxima verossimilhança. Estudos de simulação, considerando diferentes valores para os parâmetros, porcentagens de censura e tamanhos amostrais foram conduzidos com o objetivo de verificar a flexibilidade da distribuição e a adequabilidade dos resíduos no modelo de regressão. Para ilustrar, são realizadas aplicações em conjuntos de dados reais. / Providing a wider and more flexible probability distribution family is of great importance in statistical studies. In this work a new method of adding a parameter to a continuous distribution is used. In this study the generalized gamma distribution (GG) is used as base distribution. The GG distribution has, as especial cases, Weibull distribution, exponential, gamma, chi-square, among others. For this motive, it is considered a flexible distribution in data modeling procedures. The new model obtained with four parameters is called log-odd log-logistic generalized gamma (OLLGG). One of the interesting characteristics of the OLLGG model is the fact that it presents bimodality. In addition, a regression model regression model called log-odd log-logistic generalized gamma (LOLLGG) based by GG (Stacy e Mihram, 1965) is introduced. This model can be very useful when, the sampled data has a mixture of two statistical populations. Another advantage of the OLLGG distribution is the ability to present various forms for the failing rate, as increasing, as decreasing, and the shapes of bathtub or U. Explicity expressions for the moments, generating functions, mean deviations are obtained. Considering non-censored and randomly censored data, the estimates for the parameters of interest were obtained using the maximum likelihood method. Simulation studies, considering different values for the parameters, percentages of censoring and sample sizes were done in order to verify the distribuition flexibility, and the residues distrbutuon in the regression model. To illustrate, some applications using real data sets are carried out.

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在傳統的迴歸模型架構下，統計推論的進行需要假設誤差項之間相互獨立，且來自於常態分配。當理論模型假設條件無法達成的時候，排列檢定（permutation tests）這種無母數的統計方法通常會是可行的替代方法。 在以往的文獻中，應用於複迴歸模型（multiple regression）之係數排列檢定方法主要以樞紐統計量（pivotal quantity）作為檢定統計量，進而探討不同排列檢定方式的差異。本文除了採用t統計量這一個樞紐統計量作為檢定統計量的排列檢定方式外，亦納入以非樞紐統計量的迴歸係數估計量b22所建構而成的排列檢定方式，藉由蒙地卡羅模擬方法，比較以此兩類檢定方式之型一誤差（type I error）機率以及檢定力（power），並觀察其可行性以及適用時機。模擬結果顯示，在解釋變數間不相關且誤差分配較不偏斜的情形下，Freedman and Lane (1983)、Levin and Robbins (1983)、Kennedy (1995)之排列方法在樣本數大時適用b2統計量，且其檢定力較使用t2統計量高，但差異程度不大；若解釋變數間呈現高度相關，則不論誤差的偏斜狀態，Freedman and Lane (1983)、Kennedy (1995) 之排列方法於樣本數大時適用b2統計量，其檢定力結果也較使用t2統計量高，而且兩者的差異程度比起解釋變數間不相關時更加明顯。整體而言，使用t2統計量適用的場合較廣；相反的，使用b2的模擬結果則常需視樣本數大小以及解釋變數間相關性而定。 / In traditional linear models, error term are usually assumed to be independently, identically, normally distributed with mean zero and a constant variance. When the assumptions cannot meet, permutation tests can be an alternative method. Several permutation tests have been proposed to test the significance of a partial regression coefficient in a multiple regression model. t=b⁄(se(b)), an asymptotically pivotal quantity, is usually preferred and suggested as the test statistic. In this study, we take not only t statistics, but also the estimates of the partial regression coefficient as our test statistics. Their performance are compared in terms of the probability of committing a type I error and the power through the use of Monte Carlo simulation method. Situations where estimates of the partial regression coefficients may outperform t statistics are discussed.