O objetivo geral desta dissertação é traçar um panorama da evolução do dativo em -e dentro do contexto do paradigma dos demais casos morfológicos existentes no alemão e detectar prováveis fatores atuando concomitantemente na variação da (não) ocorrência desse marcador de caso. Para tanto, revisitamos o desenvolvimento do sistema de casos do alemão e descrevemos o comportamento e padrões exibidos pelos marcadores de caso de substantivos no singular e no plural. Discutimos a útil noção de declinações forte e fraca, de Grimm (1822), bem como algumas teorias sobre mudança linguística, tais como o enfraquecimento de sílabas átonas (SAPIR, 1921), o surgimento do artigo definido (PHILLIPI, 1997) e da teoria baseada no uso (BARðDAL, 2009). As questões levantadas por essas teorias podem ter contribuído com o paulatino apagamento de marcadores de caso nas línguas germânicas. Não rejeitamos nenhuma delas, haja vista que todas fornecem hipóteses plausíveis, entretanto, a mudança não ocorreu de forma homogênea em diferentes contextos e parece exibir certos padrões que podem ser explicados pela interação de diversos fatores, e não com base apenas nas grandes ideias das teorias descritas acima. Testar a hipótese dessa policausalidade requer o emprego de metodologia específica. Como o fenômeno aqui estudado é a realização vs. não realização do dativo em -e, empregamos o método de regressão logística binária, o mais adequado para descrever e testar hipóteses sobre relações entre uma variável-resposta categórica e variáveis explanatórias também categóricas e/ou contínuas (PENG; LEE; INGERSOLL, 2002). Obtivemos robusta evidência de que fatores tipológicos, fonológicos e prosódicos desempenham importante papel na variação da realização do dativo em -e e observamos que a interação de fatores tem maior poder explanatório sobre os padrões exibidos na variação do que uma análise que considere a influência de diferentes fatores de maneira isolada. A maior vantagem em aplicarmos um teste como o de regressão logística binária consiste na possibilidade de captar a existência de determinados padrões interacionais, e, portanto, podemos analisar a variação e mudança, como no exemplo do dativo em -e, de um ponto de vista multifatorial, e não limitando nosso escopo a fatores isolados, pois, em um sistema complexo como é a língua, eles parecem indissociáveis. / The main goal of this investigation is to outline an overview of the development of the dative -e within the context of the paradigm of other morphological cases existing in German and to identify factors that play a concomitant role in the variation of the (non-)occurence of the case marker. In order to perform this task, we revisited the development of the German case system and described the behaviour and patterns exhibited by the case markers of singular and plural nouns. We discussed the useful notion of strong and weak declensions such as thought of by Grimm (1822), as well as some theories on language change, as the weakening of unstressed syllables (SAPIR, 1921), the rise of the definite article (PHILLIPI, 1997) and the usage-based approach to language (BARðDAL, 2009). The questions raised within the framework of these theories might have contributed to the non-occurrence of the case marker in Germanic languages. We did not reject any of the theories, since they provide plausible hypotheses, however, the change did not occur homogeneously in different contexts and it seems to exhibit certain patterns that may be accounted for by the interaction between diverse factors and therefore not only by the general ideas mentioned above. In order to test this multicausality hypothesis, it is necessary to apply a specific methodology. Given that the phenomenon studied in this investigation is the occurrence vs. non-occurrence of the dative -e, we performed a binary logistic regression analysis, which is well suited for describing and testing hypotheses about relationships between categorical outcome variables and explanatory variables that are also categorical and/or continuous (PENG; LEE; INGERSOLL, 2002). We obtained strong evidence that typological, phonological and prosodic factors play an important role in the variation of the dative -e and we observed that the interaction between such factors can better explain the patterns exhibited in the variation than an approach that only takes into account the influence of individual factors. The advantage in performing a binary logistic regression is based on the fact that it highlights the existence of interactional factors, and therefore we can analyse the variation and change, using the example of the dative -e, from a multifactorial point of view without limiting our scope to individual factors only, since they do not seem to work individually within a complex system such as the human language.

Buried pipelines are vulnerable to the threat of corrosion. Hence, they are normally coated with a protective coating to isolate the metal substrate from the surrounding environment with the addition of CP current being applied to the pipeline surface to halt any corrosion activity that might be taking place. With time, this barrier will deteriorate which could potentially lead to corrosion of the pipe. The External Corrosion Direct Assessment (ECDA) methodology was developed with the intention of upholding the structural integrity of pipelines. Above ground indirect inspection techniques such as the DCVG which is an essential part of an ECDA, is commonly used to determine coating defect locations and measure the defect's severity. This is followed by excavation of the identified location for further examination on the extent of pipeline damage. Any coating or corrosion defect found at this stage is repaired and remediated. The location of such excavations is determined by the measurements obtained from the DCVG examination in the form of %IR and subjective inputs from experts which bases their justification on the environment and the physical characteristics of the pipeline. Whilst this seems to be a straight forward process, the factors that comes into play which gave rise to the initial %IR is not fully understood. The lack of understanding with the additional subjective inputs from the assessors has led to unnecessary excavations being conducted which has put tremendous financial strain on pipeline operators. Additionally, the threat of undiscovered defects due to the erroneous nature of the current method has the potential to severely compromise the pipeline's safe continual operation. Accurately predicting the coating defect size (TCDA) and interpretation of the indication signal (%IR) from an ECDA is important for pipeline operators to promote safety while keeping operating cost at a minimum. Furthermore, with better estimates, the uncertainty from the DCVG indication is reduced and the decisions made on the locations of excavation is better informed. However, ensuring the accuracy of these estimates does not come without challenges. These challenges include (1) the need of proper methods for large data analysis from indirect assessment and (2) uncertainty about the probability distribution of quantities. Standard mean regression models e.g. the OLS, were used but fail to take the skewness of the distributions involved into account. The aim of this thesis is thus, to come up with statistical models to better predict TCDA and to interpret the %IR from the indirect assessment of an ECDA more precisely. The pipeline data used for the analyses is based on a recent ECDA project conducted by TWI Ltd. for the Middle Eastern Oil Company (MEOC). To address the challenges highlighted above, Quantile Regression (QR) was used to comprehensively characterise the underlying distribution of the dependent variable. This can be effective for example, when determining the different effect of contributing variables towards different sizes of TCDA (different quantiles). Another useful advantage is that the technique is robust to outliers due to its reliance on absolute errors. With the traditional mean regression, the effect of contributing variables towards other quantiles of the dependent variable is ignored. Furthermore, the OLS involves the squaring of errors which makes it less robust to outliers. Other forms of QR such as the Bayesian Quantile Regression (BQR) which has the advantage of supplementing future inspection projects with prior data and the Logistic Quantile Regression (LQR) which ensures the prediction of the dependent variable is within its specified bounds was applied to the MEOC dataset. The novelty of research lies in the approaches (methods) taken by the author in producing the models highlighted above. The summary of such novelty includes: * The use of non-linear Quantile Regression (QR) with interacting variables for TCDA prediction. * The application of a regularisation procedure (LASSO) for the generalisation of the TCDA prediction model.* The usage of the Bayesian Quantile Regression (BQR) technique to estimate the %IR and TCDA. * The use of Logistic Regression as a guideline towards the probability of excavation * And finally, the use of Logistic Quantile Regression (LQR) in ensuring the predicted values are within bounds for the prediction of the %IR and POPD. Novel findings from this thesis includes: * Some degree of relationship between the DCVG technique (%IR readings) and corrosion dimension. The results of the relationship between TCDA and POPD highlights a negative trend which further supports the idea that %IR has some relation to corrosion. * Based on the findings from Chapter 4, 5 and 6 suggests that corrosion activity rate is more prominent than the growth of TCDA at its median depth. It is therefore suggested that for this set of pipelines (those belonging to MEOC) repair of coating defects should be done before the coating defect has reached its median size. To the best of the Author's knowledge, the process of employing such approaches has never been applied before towards any ECDA data. The findings from this thesis also shed some light into the stochastic nature of the evolution of corrosion pits. This was not known before and is only made possible by the usage of the approaches highlighted above. The resulting models are also of novelty since no previous model has ever been developed based on the said methods. The contribution to knowledge from this research is therefore the greater understanding of relationship between variables stated above (TCDA, %IR and POPD). With this new knowledge, one has the potential to better prioritise location of excavation and better interpret DCVG indications. With the availability of ECDA data, it is also possible to predict the magnitude of corrosion activity by using the models developed in this thesis. Furthermore, the knowledge gained here has the potential to translate into cost saving measures for pipeline operators while ensuring safety is properly addressed.

This thesis assesses the usefulness of confidence indicators for short term forecasting of the economic activity in the Czech Republic. The predictive power of both the business confidence indicator and the customer confidence indicator is examined using two empirical approaches. First we predict the likelihood of economic downturn defined as a discrete event using logit models, later we estimate GDP growth out of sample forecasts in the framework of vector autoregression models. The results obtained from the downturn probability models confirm the ability of confidence indicators (especially the business confidence indicator) to estimate the current economic situation and to anticipate economic downturn one quarter ahead. Results from the out-of-sample GDP growth value forecasting are ambiguous. Nevertheless the customer confidence indicator significantly improved original forecasts based on a model with standard macroeconomic variables and therefore we conclude in favour of its predictive power. This result was indirectly confirmed by OECD as the Czech customer confidence indicator has been included as a new component in the OECD domestic composite leading indicator since April 2012.

The urban sprawl cannot be any longer perceived as a solely esthetic and socioeconomic problem. The process of shift of population and activities from city centre to its fringe has significant environmental impacts as well. Typicaly, suburban areas are spatially and therefore energetically demanding, the landscape is being fragmented by their presence and the natural environment of organisms is severely modified or destroyed. Soil sealing and impervious surfaces lead to altered heat and moist regimes, infiltration rate and runoff. Soils at city fringe - usually very productive and valuable - are endangered by total loss of all of their functions, both environmental and agricultural. That is also the case of Prague surroundings, where high quality soils, which are supposed to be protected by the law, are irreversibly degraded by urban sprawl. Logistic regression model in this work has proved that commercial urban sprawl tends to occur in areas with a good logistic position and a level terrain. The awareness of factors, which are favorable for urban sprawl, can be utilized in future to make local planning more effective and prevent sealing of high-quality agricultural soils, which are currently built on. By sprawling on an agricultural land, Czech Republic loses its natural wealth and valuable...

O objetivo do trabalho é apresentar os métodos mais consagrados de Análise Discriminante quando temos uma mistura de variáveis categóricas e contínuas. / The purpose of this dissertation is to analyze and compare Discriminant Analysis techniques in the presence of mixed categorical and continuous data.

Modelos de credit score são usualmente desenvolvidos somente com informações dos proponentes aceitos. Neste trabalho foram consideradas estratégias que podem ser utilizadas para o desenvolvimento de modelos de credit score com a inclusão das informações dos rejeitados. Foram avaliadas as seguintes técnicas de inferência de rejeitados: classificação dos rejeitados como clientes Maus, parcelamento, dados aumentados, uso de informações de mercado e ainda a estratégia de aceitar proponentes rejeitados para acompanhamento e desenvolvimento de novos modelos de risco de crédito. Para a avaliação e comparação dos modelos foram utilizadas as medidas de desempenho: estatística de Kolmogorov-Smirnov (KS), área sob a curva de Lorentz (ROC), área entre as curvas de distribuição acumulada dos escores (AEC), diferença entre as taxas de inadimplência nos intervalos do escore definidos pelos decis e coeficiente de Gini. Concluiu-se que dentre as quatro primeiras técnicas avaliadas, o uso de informaçõoes de mercado foi a que apresentou melhor desempenho. Quanto à estratégia de aceitar proponentes rejeitados, observou-se que há um ganho em relação ao modelo ajustado só com base nos proponentes aceitos. / Credit scoring models are usually built using only information of accepted applicants. This text considered strategies that can be used to develop credit score models with inclusion of the information of the rejects. We evaluated the techniques of reject inference: classification of rejected customers as bad, parceling, augmentation, use of market information and the strategy of accepting rejected proponents for monitoring and developing new models of credit risk. For the evaluation and comparison between models were used performance measures: Kolmogorov-Smirnov statistics (KS), the area under the Lorentz Curve (ROC), area between cumulative distribution curves of the scores (AEC), difference among the delinquency rate in the score buckets based on deciles (DTI) and the Gini coefficient. We concluded that among the first four techniques evaluated, the fourth (use of market information) had the best performance. For the strategy to accept rejected bidders, it was observed that there is a gain in relation to the model that uses only information of accepted applicants.

Métodos analíticos para concessão de crédito vêm apresentando enormes avanços nas últimas décadas, particularmente no que se refere a métodos estatísticos de classificação para identificar grupos de indivíduos com diferentes taxas de inadimplência. A maioria dos trabalhos existentes sugere decisões do tipo conceder o crédito ou não, considerando apenas de forma marginal o resultado esperado da operação. O presente trabalho tem o objetivo de propor um modelo de avaliação de risco de crédito mais complexo que os tradicionais modelos de Credit Scoring, que forneça uma perspectiva mais detalhada acerca do desempenho futuro de um contrato de crédito, e que vá além da classificação entre bom e mau pagador. Aliado a este ganho de informação na previsibilidade oferecida pelo modelo, também é objetivo ampliar o espaço de decisões do problema, saindo de uma resposta binária (como aceitar/rejeitar o crédito) para algo que responda à seguinte pergunta: qual é a taxa justa para cobrir determinado risco?. / Analytical methods for granting credit are presenting enormous advances in recent decades, particularly in the field of statistical methods of classification to identify groups of individuals with different rates of default. Most of the existing work suggests decisions of the type granting credit or not, regarding just marginally the expected outcome of the operation. This work aims to propose a model to evaluate credit risk with more complexity than the traditional \"Credit Scoring\" models, providing a more detailed view about the future performance of a credit agreement, which goes beyond the classification of good and bad payers. Coupled with this improvement of information offered by the model, it is also this works aim to expand the decision space of the problem, leaving a binary response (such as accept/reject the claim) to something that answers the following question: \"what is the fair rate to cover a given risk \".

Os modelos de credit scoring têm sido bastante difundidos nos últimos anos como uma importante ferramenta para agilizar e tornar mais confiável o processo de concessão de crédito por parte das instituições financeiras. Esses modelos são utilizados para classificar os clientes em relação a seus riscos de inadimplência. Neste trabalho, é avaliada a aplicabilidade de uma nova metodologia, baseada em pseudo-valores, como alternativa para a construção de modelos de credit scoring. O objetivo é compará-la com abordagens tradicionais como a regressão logística e o modelo de riscos proporcionais de Cox. A aplicação prática é feita para dados de operações de crédito pessoal sem consignação, coletados do Sistema de Informações de Crédito do Banco Central do Brasil. As performances dos modelos são comparadas utilizando a estatística de Kolmogorov-Smirnov e a área sob a curva ROC. / Credit Scoring models have become popular in recent years as an important tool in the credit granting process, making it more expedite and reliable. The models are mainly considered to classify customers according to their default risk. In this work we evaluate the apllicability of a new methodology, based on pseudo-values, as an alternative to constructing credit scoring models. The objective is to compare this novel methodology with traditional approaches such as logistic regression and Cox proportional hazards model. The models are applied to a dataset on personal credit data, collected from the Credit Information System of Central Bank of Brazil. The performances of the models are compared via Kolmogorov-Smirnov statistic and the area under ROC curve.

Universidade Federal do Cearà / Desde o ano de 2000 que as cooperativas de crÃdito brasileiras tÃm experimentado um crescimento contÃnuo no nÃmero de novas unidades. De outro modo os bancos brasileiros tem diminuÃdo em quantidade pelo processo de aquisiÃÃo e concentraÃÃo. Este crescimento das cooperativas pode estar associado com um maior risco para os associados. Este trabalho investiga as causas de falÃncias das cooperativas de crÃdito dos profissionais de saÃde no Brasil. Para tanto busca fornecer um modelo de alerta precoce que informe aos gestores e supervisores do risco de insolvÃncia, fazendo uso de uma anÃlise de regressÃo logÃstica de Ãndices financeiros. Foi estimado um modelo de prediÃÃo de insolvÃncia que fosse parcimonioso e acurado. Este trabalho provà informaÃÃes adicionais a outros estudos brasileiros sobre falÃncia em cooperativas de crÃdito, de trÃs modos: à um estudo de abrangÃncia nacional, trata com cooperativa de crÃdito mÃtuo urbano, usa uma moderna tÃcnica estatÃstica com dados em painel, o que permite capturar as diferenÃas entre as cooperativas. O presente estudo tambÃm fornece uma maneira racional para a escolha do cut-off. Os resultados sugerem que provisÃo para emprÃstimo em atraso para total do ativo, Total de emprÃstimo para Total de ativo, Total de emprÃstimo para Total de depÃsitos e PatrimÃnio LÃquido Passivo total, sÃo os preditores mais significativos da insolvÃncias das cooperativas. De modo contrÃrio as Despesas Operacionais para Receitas Operacionais e Despesas Operacionais para ativo total nÃo indicam ser significativas em prever a insolvÃncia. / Since the year of 2000 Brazilians credit cooperatives has experienced a increasing growth in number of units. On the other hand Brazilians banks decreased their number, by the process of acquisition and concentration. This growth may imply increasing risk for the associates. This paper empirically investigates the causes of failures of credit cooperatives of heath professionals in Brazil. A goal of this paper is provide a early warning model that inform managers and supervisors of a risks of default, by using logistic regression analysis of financial ratios. It was estimate a default prediction model that was parsimonious and accurate. This work provided additional information over other Brazilian studies of credit cooperatives failure by three ways: it is a national wide study, deals with urban mutual credit cooperative, uses modern statistic technique panel data which can capture the differences across cooperatives. It also provided a reasonable for the choosing of cut-off. The results suggest that provision for bad debts over total assets, total loans over total assets, total loans over total deposits are the most significant predictors of credit cooperative failure. Operational expenses over operational incomes and operational expenses over total assets, contrary, do not seem to be significant indicators of failure

Universidade Federal do Cearà / Este trabalho tem o objetivo de desenvolver um estudo de caso sobre o fenÃmeno da evasÃo no ensino superior de uma universidade em particular. No Ãmbito internacional, a evasÃo no ensino superior tem sido bastante discutida. No Brasil, esta temÃtica vem sendo objeto de estudo cientÃfico desde a dÃcada de 80, e em mÃdia verificamos uma grande quantidade de estudos particularizados. A partir dos dados obtidos junto a uma InstituiÃÃo de Ensino Superior, a Universidade de Fortaleza â Unifor, situada na cidade de Fortaleza - CearÃ, esta dissertaÃÃo propÃs estudar o fato do aluno evadir ou nÃo o seu curso de graduaÃÃo. O mÃtodo utilizado para o desenvolvimento do trabalho foi uma coleta de dados proveniente do sistema acadÃmico e questionÃrio sÃcio econÃmico, no qual configurados em uma planilha matriz foi possÃvel diagnosticar o fenÃmeno da evasÃo. Este trabalho desenvolveu e aplicou uma metodologia baseada no modelo de regressÃo logÃstica com o intuito de observar a evasÃo no ensino superior e o perÃodo estudado foi 1994.2 atà 2004.1. O resultado encontrado nos revelou que a variÃvel dummy evasÃo està diretamente relacionada as variÃveis independente sexo, estado civil, escolaridade do aluno, remuneraÃÃo do aluno e os centros dos cursos de graduaÃÃo. Entretanto, as variÃveis sexo e renda do aluno foram as estatisticamente mais significativas no processo de decisÃo do aluno evadir ou nÃo. Para reduzir a evasÃo, a universidade deverà implantar um sistema que possa avaliar a satisfaÃÃo do aluno em relaÃÃo à universidade como, tambÃm, buscar identificar quais sÃo as maiores dificuldades encontradas pelos alunos a fim de reduzir a evasÃo dos mesmos. / This work aimed to produce a case study about evasion of undergraduate students in a particular university. Data was obtained from the Universidade de Fortaleza - Unifor, located at Fortaleza, state of CearÃ, Brazil. This dissertation was proposed to investigate whether the student evades or not his/her undergratuate course. To achieve its goal, the work developed a logistic econometric model by which it was observed that evasion is related directly to independent variables: sex, civil states, studentâs scholarship, studentâs earnings, areas of knowledge in this case study.