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Lapse Analysis of Insurance Contracts
Strnad, Jan ; Mertl, Jakub (advisor) ; Mazurová, Lucie (referee)
The aim of the present work is to develop a tool for identification of Motor Third Party Liability insurance contracts which are at risk of cancellation. Methods for explorative data analysis, building a logistic regression model, comparing models and their validation and calibration are presented. Several models are developed on the real dataset using mentioned methods and then the final one is chosen. Behavior of the final model is verified by the validation on the out-of-time sample. Last step is calibration of the model to the expected value of the future portfolio cancellation rate.
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Vehicle classification using inductive loops sensors
Halachkin, Aliaksei ; Klečka, Jan (referee) ; Honec, Peter (advisor)
This project is dedicated to the problem of vehicle classification using inductive loop sensors. We created the dataset that contains more than 11000 labeled inductive loop signatures collected at different times and from different parts of the world. Multiple classification methods and their optimizations were employed to the vehicle classification. Final model that combines K-nearest neighbors and logistic regression achieves 94\% accuracy on classification scheme with 9 classes. The vehicle classifier was implemented in C++.
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Application of (geo)demographic methods in education
Šebestík, Libor ; Hulíková Tesárková, Klára (advisor) ; Fialová, Ludmila (referee)
Application of (geo)demographic methods in education Abstract This master's thesis presents the possibilities of application of demographic, geodemographic and statistical methods on data published by the educational sector. The methods of demographic analysis are represented by the usage of rates, the concept of multistate demography (Markov chains) and the application of life tables. The enrollment ratio at particular levels of education, the average length of schooling and the number of dropouts from school grades are evaluated by these procedures. Markov chains which are based on the probabilities of transition between grades are also examined in terms of their use for forecasting purposes. These methods analyze the situation at the preschool, primary and secondary levels and are used on data from the annual Statistical Yearbooks on Education. In the field of geodemography, the so called preferential model of migration flows is presented. This model examines how applicants for tertiary education prefer or reject the regions of the Czech Republic for their tertiary education studies. The last method is the binary logistic regression which analyzes the inequalities in access to tertiary education. Both preferential model and logistic regression are based on data files on the admission process at...
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Impact of commercial urban sprawl on soil cover on the outskirts of Prague and its future predictions
Havel, Petr ; Chuman, Tomáš (advisor) ; Romportl, Dušan (referee)
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...
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Regression goodness-of-fit criteria according to dependent variable type
Šimsa, Filip ; Hanzák, Tomáš (advisor) ; Hlubinka, Daniel (referee)
This work is devoted to the description of linear, logistic, ordinal and multinominal regression models and interpretation of its parameters. Then it introduces a variety of quality indicators of mathematical models and the re- lations between them. It focuses mainly on the Gini coefficient and the coefficient of determination R2 . The first mentioned is established by modifying the Lorenz curve for ordinal and continuous variables and by comparing the estimated proba- bilities for nominal variable. The coefficient of determination R2 is newly defined for the nominal variable and is examined its relationship with Gini coefficient. As- suming normally distributed scores and errors of the model is numerically derived the relation between the Gini coefficient and the coefficient of determiantion for different distribution of continuous dependent variable. Theoretical calculations and definitions are illustrated on two real data sets. 1
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Forecasting Ability of Confidence Indicators: Evidence for the Czech Republic
Herrmannová, Lenka ; Horváth, Roman (advisor) ; Mikolášek, Jakub (referee)
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.
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Comparison of logistic regression and decision trees
Raadová, Zuzana ; Voříšek, Jan (advisor) ; Komárek, Arnošt (referee)
In this thesis we describe a classification of the binary data. For discussing this problem we use two well-known methods - logistic regression and decision trees. These methods deal with the problem in different way, so our aim is to compare a successfulness of their predictions. At first a model of logistic regression is introduced and we show how to estimate its parameters using a method of maximum likelihood. Then we describe decision trees as one of the most popular classification tools. There are discussed older classic algorithms CART and C4.5 and also two new algorithms GUEST and CRUISE. The predictions of both of the methods are shown on a real data example.
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Ethnic groups in the former Soviet Union space
Tkáčová, Kateřina ; Plechanovová, Běla (advisor) ; Střítecký, Vít (referee)
The topic of this diploma thesis is ethnic groups in the space of the former Soviet Union in the time period 1994-2006 and their involvement in ethnic conflicts. The aim of this thesis is to identify key parameters driving these ethnic groups towards armed conflict as a response to their needs, interests and living conditions. Key assumptions of this thesis are derived from qauntitative as well as qualitative studies. Important characteristics of ethnic groups are also included in the analysis of possible causes of ethnic conflicts. The theoretical discussion shows three main factors which can make ethnic groups more prone to conflict: permanent exclusion, strong identity and lastly dissimilarity of an ethnic group. Influence of these factors is tested using descriptive statistics, odds ratio, correlation and logistic regression. Statistical results shows that strong identity as well as discrimination of ethnic groups increase the probability of ethnic conflicts.
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Late matherhood from demographic point of view (example of The Czech and Slovak Republic)
Vobořilová, Michaela ; Fialová, Ludmila (advisor) ; Bartoňová, Dagmar (referee)
Late Motherhood from Demographic Point of View (Example of the Czech and Slovak Republic) Abstract The thesis thematically refers the issue of late motherhood in the Czech and Slovak Republics from the twenties of the twentieth century to the present from a demographic point of view. It describes the changes that have occurred during the observed years as to fertility of women aged over 35, using selected demographic indicators. In the second part the focus lies on the analysis of selected demographic factors using binary logistic regression. In the very end, the form of late motherhood is discussed. According to the results of the analysis are determined three different types of late motherhood. Keywords: late motherhood, late maternity, fertility, Czech Republic, Slovak Republic, logistic regression
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