National Repository of Grey Literature 105 records found  previous11 - 20nextend  jump to record: Search took 0.02 seconds. 
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
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...
Fertility postponement in the Czech Republic and selected European countries in the period 1990−2015
Tovarová, Lenka ; Kurtinová, Olga (advisor) ; Šťastná, Anna (referee)
Fertility postponement in the Czech republic and selected European countries in the period 1990−2015 Abstract We have been able to observe the trend of shifting of maternity to later periods of life in European countries since the second half of the 20th century. However crucial for this thesis is to determine whether there have been disparity in delaying of maternity between selected Eastern European (Czech Republic, Slovakia, Poland) and Western European (Germany and Austria) countries since 1990 till present. The goal of this work is to find the relationship among setting of family policies, fertility rate of older women and respondents' views. In the first part of this thesis are outlined basic theories explaining postponing of maternity. There are also listed consequences related to the late maternity. The thesis touches a topic of family policies which influence the phenomenon of late maternity. It presents several fundamental tools of family policies and compares them among selected countries. The second part focuses on a description of demographic indicators that demonstrate the shift in timing of maternity. The main analysis in this thesis is a logistic regression, which explains respondent's views on issues related to a harmonization of family and employment by selected explanatory variables from...
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
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.
Regional Convergence in the European Union: Do the Business Services Make the Difference?
Pintera, Jan ; Baxa, Jaromír (advisor) ; Kopečná, Vědunka (referee)
Despite years of deepening economic integration among the states and regions of the European Union, empirical research remains inconclusive about speed of convergence across regions, if not its existence. This thesis provides novel evidence on convergence in the EU while focusing on development at regional level after the Great Recession. It uses recently developed log t convergence test by Phillips and Sul (2007). Our findings speak against the convergence in level of income per capita among the European regions and give us five clubs of regions converging in their income growth rates instead. Investigating further the geographical distribution of the convergence clubs, we confirm high inequality within the member states and find large continuous area of high convergence clubs in the urbanized part of Western Europe. Furthermore, we investigated the determinants of convergence club membership using Logistic Regression. The main explanatory variable of interest were Business Services (BS), a dynamic sector of the economy with presumably strong positive effect on regional innovative potential. We found positive effect of BS on membership in higher convergence clubs. Yet, this effect seems to diminish for the very highest club.
Forecasting and nowcasting power of confidence indikators:Evidence for Central Europe
Herrmannová, Lenka ; Horváth, Roman (advisor) ; Mikolášek, Jakub (referee)
This thesis assesses the usefulness of confidence indicators for nowcasting and short term forecasting of the economic activity in the Czech Republic and three other Central European countries. The predictive power of both the Czech business confidence indicator and the customer confidence indicator is examined using two empirical approaches. First we predict the likelihood of economic downturn 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, so called nowcast. Results from the out-of-sample GDP growth value forecasting are ambiguous. Nevertheless the customer confidence indicator significantly improved original forecasts based on the model with standard macroeconomic variables and therefore we conclude in favour of its predictive power. Cross- country comparison confirms economic downturn nowcasting power of confidence indices in Hungary and Poland and fails to confirm such an ability of Slovak confidence indicators. One-quarter-ahead forecasts brought mixed results and therefore we conclude that nowcasting and forecasting properties of...
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.
Voters and Non-voters in the Czech Republic
Vavřinová, Tereza ; Linek, Lukáš (advisor) ; Hendl, Jan (referee)
This study discusses voting behavior of the citizens in The Czech republic. Traditional studies of voting behavior differentiate between voters and nonvoters according to their turnout in one election. This thesis takes up multielection approach and differentiates three categories of voting behavior- voters, nonvoters and irregular voters. Specific features of voters, nonvoters and irregular voters are identified using logistic regression analysis. Theoretically, the study is based on socioeconomic, motivational and mobilization theories of turnout. The focus is put on the decision making of irregular voters. Circumstances tied with irregular voters' turnout are identified. The discussion on methodological problems connected with multi-election approach and research of electoral behavior generally is part of the thesis. The Czech election study 2010 is a main source of the data for analysis.
Discrimination measures in credit risk
Polak, Michal ; Pešta, Michal (advisor) ; Zahradník, Petr (referee)
Scoring models represent a fundamental tool for the modern management of credit risk. This is mainly due to a significant development in the field of information technology. Such models are used not only when providing credit, but also in strategies relating to the future management of credit risk, or in strategies connected with enforcing receivables. In my thesis I deal with discrimination measures used in the validation of diversification potential of logistic scoring models. At the beginning, I focus on the term 'risk'. Then, I introduce a basic division of scoring models. Next, I describe the method of scoring logistic regression, I concentrate on estimating parameters, their significance and on testing their relevance. For the measurement and illustration of diversification potential of the model I mention the most commonly used methods such as the Lorenz and ROC curve, the Gini coeficient, the c-statistic as well as the Kolmogorov-Smirnov test. Finally, I apply the theoretical knowledge to real data. I design a scoring model and subsequently compare the discrimination measures which it contains. Powered by TCPDF (www.tcpdf.org)

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