National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Stable distributions and their applications
Volchenkova, Irina ; Klebanov, Lev (advisor) ; Beneš, Viktor (referee)
The aim of this thesis is to show that the use of heavy-tailed distributions in finance is theoretically unfounded and may cause significant misunderstandings and fallacies in model interpretation. The main reason seems to be a wrong understanding of the concept of the distributional tail. Also in models based on real data it seems more reasonable to concentrate on the central part of the distribution not tails. Powered by TCPDF (www.tcpdf.org)
Regression methods in statistical software
Volchenkova, Irina ; Legát, David (advisor) ; Antoch, Jaromír (referee)
b;g;igpiipu.txt[24.05.2013 12:17:27] Title: Regression methods in statistical software Author: Irina Volchenkova Department: Department of Probability and Mathematical Statistics Supervisor: Mgr. David Legát, Ph.D., Department of Probability and Mathematical Statistics Abstract: Regression analysis is a useful instrument for data mining. This thesis contains detailed information about linear regression especially about the mean least squares method. The theoretical part is divided into two parts: general theoretical introduction of the first part explains parameters, abilities and usage of mean least squares method; several algorithms for numerical solving of linear equation systems. Three ordinally used statistical softwares are described in the last part of the diploma thesis: MatLab, software R, SPSS. These softwares were chosen to represent the whole spectrum of all existed statistical programs. Keywords: regression analysis, linear regression, regression, least mean squares method, statistical softwares.

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