Regression analysis is one of the most extensively used statistical tools applied across different fields of science, with linear regression being its most well-known method. How- ever, the traditional procedure to obtain the linear model estimates, the least squares approach, is highly sensitive to even slight departures from the assumed modelling frame- work. This is especially pronounced when atypical values occur in the observed data. This lack of stability of the least squares approach is a serious problem in applications. Thus, the focus of this thesis lies in assessing the available robust alternatives to least squares estimation, which are not so easily affected by any outlying values. First, we introduce the linear regression model theory and derive the least squares method. Then, we char- acterise different types of unusual observations and outline some fundamental robustness measures. Next, we define and examine the robust alternatives to the classical estimation in the linear regression models. Finally, we conduct a comprehensive simulation study comparing the performance of robust methods under different scenarios. 1

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20688号 / 工博第4385号 / 新制||工||1681(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 三ｹ田 均, 准教授 須崎 純一 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The primary objective of this study is to evaluate the operational effects of U-turn movement at signalized intersections. More specifically, the research objectives include the following parts: To identify the factors affecting the operational performance of U-turning vehicles. In this case, we are particularly interested in the U-turn speeds of U-turning vehicles. To evaluate the impacts of U-turns on capacity of signalized intersections, and To simulate U-turn movement at signalized intersections using Synchro and validate the simulation results. To achieve the research objectives, extensive field data collection work was conducted at sixteen selected sites at Tampa Bay area of Florida. The data collected in the field include: U-turning speed Left turning speed Turning radius Queue discharge time Control delay Hourly traffic volume, and Percentage of U- turning vehicles in left turn lane. Based on the collected field data, a linear regression model was developed to identify the factors affecting the turning speeds of U-turning vehicles at signalized intersections. The model shows the turning speed is significantly impacted by the turning radius and the speed of U-turning vehicles increases with the increase of turning radius. On the basis of field data field data collection, a regression model was developed to estimate the relationship between the average queue discharge time for each turning vehicle and the various percentages of U-turning vehicles in the left turn traffic stream. Adjustment factors for various percentages of U-turning vehicles were also developed by using the regression model. The adjustment factors developed in this study can be directly used to estimate the capacity reduction due to the presence of various percentages of U-turning vehicles at a signalized intersection. The developed adjustment factors were used to improve the simulation of U-turn movement at signalized intersection by using Synchro. The simulation model was calibrated and validated by field data. It was found that using the developed adjustment factors will greatly improve the accuracy of the simulation results for U-turn movement.

nÃo hà / This work aims to raise the fundraising potential of the ISS as a main source of revenue each municipality's MaracanaÃ. The analysis was the main source of information crossing the Department of Finance in relation to the collection of the ISS in the years 2006 to 2010 (base SEFIN) and base register of the IRS and the Board of Trade of the State of CearÃ. Comparing databases, there is, from the outset, a much larger base of taxpayers the IRS and the Board of Trade that the base of SEFIN. Thus, in view of the possibility of an increase in the collection, it was decided to search this potential through a linear regression model, assuming as the dependent variable and independent variables fundraising capital, type of company (provider or receiver service) and business size (large or small), both variables with explanatory power. We conclude that in MaracanaÃ, studies showed that there is great potential for revenue collection in the ISS. / Com este trabalho pretendeu-se levantar o potencial de arrecadaÃÃo do ISSQN como fonte principal da receita prÃpria do municÃpio de MaracanaÃ. A anÃlise teve como fonte principal o cruzamento das informaÃÃes da Secretaria de FinanÃas no que se refere à arrecadaÃÃo do ISSQN nos anos de 2006 a 2010 (base SEFIN) e a base cadastral da Receita Federal e da Junta Comercial do Estado do CearÃ. Comparando as bases de dados, observa-se, jà de inÃcio, uma quantidade muito maior de contribuintes na base da Receita Federal e da Junta Comercial do que na base da SEFIN. Dessa forma, tendo em vista a possibilidade de incremento na arrecadaÃÃo, resolveu-se pesquisar esse potencial por meio de um modelo de regressÃo linear, assumindo como variÃvel dependente a arrecadaÃÃo e como variÃveis independentes o capital social, o tipo de empresa (prestadora ou tomadora de serviÃo) e o porte empresarial (pequeno ou grande porte), ambas como variÃveis com poder de explicaÃÃo. Conclui-se que no municÃpio de MaracanaÃ, os estudos apontaram que existe um grande potencial de arrecadaÃÃo no recolhimento do ISSQN.

The goal of this thesis is introduce the theory of generalized linear models, namely probit and logit model. This models are especially used for medical data processing. In our concrete case these mentioned models are applied to data file obtained in teaching hospital Brno. The aim is statically analyzed immune response of child patients in dependence of twelve selected types of genes and find out which combinations of these genes influence septic state of patients.

This thesis sumarizes in detail general linear regression model, including testing statistics for coefficients, submodels, predictions and mostly tests of outliers and large leverage points. It describes how to include categorial variables into regression model. This model was applied to describe saturation of photographs of bread, where input variables were, type of flour, type of addition and concntration of flour. After identification of outliers it was possible to create mathematical model with high coefficient of determination, which will be usefull for experts in food industry for preliminar identification of possible composition of bread.

Die Kapitel 1 bis 6 im ersten Teil dieses Skriptes beruhen auf einer Vorlesung Ökonometrie I, die zuletzt im WS 2001/02 gehalten wurde, die Kapitel 7 bis 16 beruhen auf einer Vorlesung Ökonometrie II, die zuletzt im SS 2006 gehalten wurde. Das achte Kapitel enthält eine komprimierte Zusammenfassung der Ergebnisse aus dem Teil Ökonometrie I.

The purpose of this thesis is to investigate further whether oil price has an effect on house price inflation and additionally if it has a link to house price turning points. The methodology is grounded on the previous research paper made by Breitenfellner et al. (2015). The results are based on quarterly data from the countries; Finland, Denmark, Norway and Sweden through the time span of 1990-2018. A linear fixed regression model was performed including the explanatory variables of monetary policy and credit developments, macroeconomic fundamentals, housing market variable and demographic variables. Secondly, a logit model was used to identify a relationship between oil price and house price turning points. The model used misalignment made from GDP per capita and real interest rate. The empirical analysis confirms that there is a positive relationship between oil prices and house price inflation. This evidence contradicts a major share of previous research papers (see Bernanke, 2010; Kaufmann et al., 2011). However, there are also some previous papers (see Yiqi, (2017); Antonakakis et al., 2016) and theoretical linkages in line with a positive correlation. Concerning, the oil price and house price inflation no empirical significance was found regarding their relationship. For future research, one could include regional aspects for the purpose of controlling for geographical differences.

This thesis analyzes the impact of the monetary policy of the Czech Republic on the Czech banking sector. It explains the monetary transmission mechanism in an inflation targeting regime and its channels: interest rates channel, asset price channel, exchange rate channel and credit channel. The aim of the thesis is to introduce and analyze channels of the Czech transmission mechanism by Correlation and Graphical Analysis of chosen time series and using Linear Regression Model. The analyses are calculated in MS Excel and Gretl.

Na tentativa de contornar os problemas ainda existentes para a detecção e identificação de erros grosseiros (EGs) no processo de estimação de estado em sistemas elétricos de potência (EESEP), realiza-se, neste trabalho, uma análise da formulação dos estimadores aplicados a sistemas elétricos de potência, em especial, o de mínimos quadrados ponderados, tendo em vista evidenciar as limitações dos mesmos para o tratamento de EGs. Em razão da dificuldade de detectar EGs em medidas pontos de alavancamento, foram também analisadas as metodologias desenvolvidas para identificação de medidas pontos de alavancamento. Através da formulação do processo de EESEP como um problema de álgebra linear, demonstra-se o porquê da impossibilidade de detectar EGs em determinadas medidas redundantes, sendo proposto, na seqüência, um método para identificação de medidas pontos de alavancamento. Para reduzir os efeitos maléficos dessas medidas no processo de EESEP verifica-se a possibilidade de aplicar outras técnicas estatísticas para o processamento de EGs, bem como técnicas para obtenção de uma matriz de ponderação adequada. / To overcome the problems still existent for gross errors (GEs) detection and identification in the process of power system state estimation (PSSE), the formulations of the estimators applied to power systems are analyzed, specially, the formulation of the weighted squares estimator. These analyses were performed to show the limitations of these estimators for GEs processing. As leverage points (LP) represent a problem for GEs processing, methodologies for LP identification were also verified. By means of the linear formulation of the PSSE process, the reason for the impossibility of GEs detection in some redundant measurements is shown and a method for LP identification is proposed. To minimize the bad effects of the LP to the PSSE process, the possibility of applying other statistic techniques for GEs processing, as well as techniques to estimate an weighting matrix are also analyzed.