|
|
Sources of economic data in the world and the possibilities of their treatment with the R software
SVOBODA, Marek
The main target of this bachelor thesis is to describe acquiring economic data from the online sources and show examples of processing the data in program R. The theoretical part of this thesis presents ten online sources of economic data and basic information about program R and programming language R. The sources that are described here are The World Bank Data, United Nations Data, IMF Data, WTO Data, OECD Data, The World Factbook (by CIA), Wolfram|Aplha, Eurostat, Czech Statistical Office and Quandl. The operator of each source is briefly introduced and then the possibilities of acquiring data for each source are described. The practical part of the thesis presents four libraries in program R which are focused on acquiring data. The libraries which are described here are WDI, eurostat, wbstats and Quandl. The possibilities of acquiring data and practical usage of methods the library provides in program R are shown for each library. Then the examples of transforming and processing the acquired data in program R are described.
|
|
|
Volatility Modelling of the Selected Stock Market
VRÁNOVÁ, Eliška
The diploma thesis deals with modelling of time series (stock and commodities) by using the models of volatility. The theoretical part focuses on the term of volatility and other terms connected to it. There is a theoretical description of the models as well. The practical part of the thesis focuses on the analysis of the time series and modelling of volatility using the program R.
|
|
|
Nonlinear regression in R programming langure
Dolák, Martin ; Malá, Ivana (advisor) ; Bašta, Milan (referee)
This thesis deals with solutions of nonlinear regression problems using R programming language. The introductory theoretical part is devoted to familiarization with the principles of solving nonlinear regression models and of their applications in the program R. In both, theoretical and practical part, the most famous and used differentiator algorithms are presented, particularly the Gauss-Newton's and of the steepest descent method, for estimating the parameters of nonlinear regression. Further, in the practical part, there are some demo solutions of particular tasks using nonlinear regression methods. Overall, a large number of graphs processed by the author is used in this thesis for better comprehension.
|
|
| |
|
|
Possibilities of use of program R in the regression and contingency Possibilities of use of program R in the regression and contingency analysis
Ballarinová, Marie ; Blatná, Dagmar (advisor) ; Plašil, Miloslav (referee)
The aim of this bachelor thesis is to introduce the basics of the statistical program R and its application to regression and contingency analysis. The work focuses on basic user skills with data processing in the program R. The program is evaluated from many perspectives (eg, program benefits, data processing in R, working with PivotTables in R, graphs in R, import and export data, etc. .). Both analyses in this work are used for demonstration of commands and syntax for these statistics. The contribution of this work is to raise awareness about the great usefulness of the program and highlight the different functions both the analysis and the basis for statistical data processing. The main part of this work is focused on commands that can be applied directly to the command line in R in practice. The structure is divided into five main chapters. The first and second chapters provide a basic description of regression analysis and contingency. The third chapter introduces the syntax, commands and technical aspects of the program R. In the fourth and fifth chapter is application of both analyses in the program R. In the regression analysis is used simple and multiple regression analysis. The main scope of contingency analysis is working with data using tables in the program R.
|
guest ::
