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Statistical Modelling of Air Pollution by Dust Aerosol
Čampulová, Martina ; Karpíšek, Zdeněk (referee) ; Michálek, Jaroslav (advisor)
The diploma thesis deals with multivariate statistical methods and their environmental applications. The theoretical part is devoted to selected methods of linear regression analysis, method of principal components and the model of classical and robust factor analysis is also described. In the practical part of thesis, the main emission sources of PM1 aerosols in summer and winter period in Brno and Šlapanice are determined by using the classical factor analysis. The main aerosol emission sources in summer and winter in Šlapanice are also identified by using the robust factor analysis. Furthermore, the prediction of concentrations of PM1 aerosols in summer and winter period in Brno and Šlapanice is performed by using the linear regression model.
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Possibilities of using multi - dimensional statistical analyses methods when evaluating reliability of distribution networks
Geschwinder, Lukáš ; Skala, Petr (referee) ; Blažek, Vladimír (advisor)
The aim of this study is evaluation of using multi-dimensional statistical analyses methods as a tool for simulations of reliability of distribution network. Prefered methods are a cluster analysis (CLU) and a principal component analysis (PCA). CLU is used for a division of objects on the basis of their signs and a calculation of the distance between objects into groups whose characteristics should be similar. The readout can reveal a secret structure in data. PCA is used for a location of a structure in signs of multi-dimensional matrix data. Signs present separate quantities describing the given object. PCA uses a dissolution of a primary matrix data to structural and noise matrix data. It concerns the transformation of primary matrix data into new grid system of principal components. New conversion data are called a score. Principal components generating orthogonal system of new position. Distribution network from the aspect of reliability can be characterized by a number of new statistical quantities. Reliability indicators might be: interruption numbers, interruption time. Integral reliability indicators might be: system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI). In conclusion, there is a comparison of performed SAIFI simulation according to negatively binomial division and provided values from a distribution company. It is performed a test at description of sign dependences and outlet divisions.
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Analysis of EEG signals
Bartošovský, Petr ; Dlouhý, Jiří (referee) ; Rozman, Jiří (advisor)
BARTOŠOVSKÝ, P. Analysis of EEG signals. Brno: Brno university of technology, Faculty of electrical engineering and communication, 2008. 35 p. Supervisor of bachelor’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with EEG signal analysis and methods of their digital processing. So-called artifacts can distort data measured during brain activity. These data were basis for comparison of two methods: The Principal Component Analysis and The Independent Component Analysis for Artifact elimination. Both methods were compared and results evaluated.
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Interest Rate Risk Analysis by Principal Component Method
Myšičková, Ivana ; Houfková, Lucia (advisor) ; Prášková, Zuzana (referee)
Presented study analyzes interest rate risk associated with the possession of given fixed coupon bond. In the first chapter, we define some of the basic concepts and provide description of available data. These are historical data on spot interest rates of zero-coupon bonds for various times to maturity which will be used for the construction of the yield curves. Based on these bond yield curves we evaluate the bond, thus obtaining a picture of the evolution of its price. Later on, we try to estimate its price tomorrow. We present two approaches how to deal with this problem. First approach is the normal interest rate risk analysis based on duration and convexity, second approach is the method of principal components which will be applied to the historical daily changes in yield curves. The method of principal components is introduced in detail.
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Analysis of financial time series with economical news headlines
Kalibán, František ; Petrásek, Jakub (advisor) ; Zichová, Jitka (referee)
This thesis is focused on options of improving the estimate of volatility of the given financial time series by analysing the economical news headlines. Because of very large volume of data and correlation between word occurence in headlines, the Principal Component Analysis is used to reduce the dimension of data space. For the elimination of significantly large skewness of dependent variable and the preservation of its normality a Box-Cox transformation is used. Finally, a linear model is constructed and its robustness is analyzed by cross-validation method. The computations were made by R software.
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Analysis of financial time series with economical news headlines
Kalibán, František ; Petrásek, Jakub (advisor) ; Zichová, Jitka (referee)
This thesis is focused on options of improving the estimate of volatility of the given financial time series by analysing the economical news headlines. Because of very large volume of data and correlation between word occurence in headlines, the Principal Component Analysis is used to reduce the dimension of data space. For the elimination of significantly large skewness of dependent variable and the preservation of its normality a Box-Cox transformation is used. Finally, a linear model is constructed and its robustness is analyzed by cross-validation method. The computations were made by R software.
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Interest Rate Risk Analysis by Principal Component Method
Myšičková, Ivana ; Houfková, Lucia (advisor) ; Prášková, Zuzana (referee)
Presented study analyzes interest rate risk associated with the possession of given fixed coupon bond. In the first chapter, we define some of the basic concepts and provide description of available data. These are historical data on spot interest rates of zero-coupon bonds for various times to maturity which will be used for the construction of the yield curves. Based on these bond yield curves we evaluate the bond, thus obtaining a picture of the evolution of its price. Later on, we try to estimate its price tomorrow. We present two approaches how to deal with this problem. First approach is the normal interest rate risk analysis based on duration and convexity, second approach is the method of principal components which will be applied to the historical daily changes in yield curves. The method of principal components is introduced in detail.
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Nowcasting the Czech Trade Balance
Babecká Kucharčuková, Oxana ; Brůha, Jan
The Working Paper Series of the Czech National Bank (CNB) is intended to disseminate the results of the CNB’s research projects as well as the other research activities of both the staff of the CNB and collaborating outside contributors, including invited speakers. The Series aims to present original research contributions relevant to central banks. It is refereed internationally. The referee process is managed by the CNB Research Department. The working papers are circulated to stimulate discussion. The views expressed are those of the authors and do not necessarily reflect the official views of the CNB.
Fulltext:  PDF
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Statistical Modelling of Air Pollution by Dust Aerosol
Čampulová, Martina ; Karpíšek, Zdeněk (referee) ; Michálek, Jaroslav (advisor)
The diploma thesis deals with multivariate statistical methods and their environmental applications. The theoretical part is devoted to selected methods of linear regression analysis, method of principal components and the model of classical and robust factor analysis is also described. In the practical part of thesis, the main emission sources of PM1 aerosols in summer and winter period in Brno and Šlapanice are determined by using the classical factor analysis. The main aerosol emission sources in summer and winter in Šlapanice are also identified by using the robust factor analysis. Furthermore, the prediction of concentrations of PM1 aerosols in summer and winter period in Brno and Šlapanice is performed by using the linear regression model.
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Analysis of EEG signals
Bartošovský, Petr ; Dlouhý, Jiří (referee) ; Rozman, Jiří (advisor)
BARTOŠOVSKÝ, P. Analysis of EEG signals. Brno: Brno university of technology, Faculty of electrical engineering and communication, 2008. 35 p. Supervisor of bachelor’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with EEG signal analysis and methods of their digital processing. So-called artifacts can distort data measured during brain activity. These data were basis for comparison of two methods: The Principal Component Analysis and The Independent Component Analysis for Artifact elimination. Both methods were compared and results evaluated.
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