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Looking for an optimal aiming point in playing darts
Mareček, Petr ; Rajmic, Pavel (referee) ; Mangová, Marie (advisor)
The thesis deals with recommendation optimal point of dartboard. The first part is theoretical, where is described issue of probability, distribution of variation and significant distribution of variation. At the end of theoretical part is described the Fourier transfrom. The second part of the thesis deals with the design and implementation of web application. The design and implemention of web application uses the theoretical part for assigment optimal point of dartboard.
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Recognition of Poses and Gestures
Jiřík, Leoš ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis inquires the existing methods on the field of image recognition with regards to gesture recognition. Some methods have been chosen for deeper study and these are to be discussed later on. The second part goes in for the concenpt of an algorithm that would be able of robust gesture recognition based on data acquired within the AMI and M4 projects. A new ways to achieve precise information on participants position are suggested along with dynamic data processing approaches toward recognition. As an alternative, recognition using Gaussian Mixture Models and periodicity analysis are brought in. The gesture class in focus are speech supporting gestures. The last part demonstrates the results and discusses future work.
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Semi - infinite programming: theory and portfolio efficiency application
Klouda, Lukáš ; Kopa, Miloš (advisor) ; Lachout, Petr (referee)
Title: Semi-infinite programming: theory and portfolio efficiency application Author: Bc. Lukáš Klouda Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Ing. Miloš Kopa, PhD. Supervisor's e-mail address: kopa@karlin.mff.cuni.cz Abstract: The thesis deals with application of semi-infinite programming to a portfolio efficiency testing. The summary of semi-infinite programming, first and second order optimality conditions and duality in linear semi-infinite programming is presented. The optimization problem for a portfolio efficiency testing with respect to the second order stochastic dominance under assumption of discrete, normal, Students and general elliptical distribution is formulated. Conditional value at risk(CVaR) is used as the risk measure, because of its consistency with the second order stochastic dominance relation. Efficiency of index PX with respect to the second order stochastic dominance is tested. The tests are performed using the program GAMS.
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Confidence Intervals for Quantiles
Horejšová, Markéta ; Kulich, Michal (advisor) ; Hlávka, Zdeněk (referee)
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are explained. Among nonparametric approaches, a special emphasis is dedicated to a recent method based on a multinomial distribution for calculating the overall confidence level of confidence intervals for all quantiles of interest using an efficient recursive algorithm, which is also described. Furthermore, a method based on Kolmogorov-Smirnov statistic or an asymptotic method using empirical distribution function and order statistics for quantile estimate are presented. A special parametric method for several quantiles of a normally distributed population is introduced along with a few of its modifications. Subsequently, a simulation is run to test the real coverage of the described theoretical methods. Powered by TCPDF (www.tcpdf.org)
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High-order stochastic dominance
Mikulka, Jakub ; Kopa, Miloš (advisor) ; Branda, Martin (referee)
The thesis deals with high-order stochastic dominance of random variables and portfolios. The summary of findings about high-order stochastic dominance and portfolio efficiency is presented. As a main part of the thesis it is proven that under assumption of both normal and gamma distribution the infinite-order stochastic dominance is equivalent to the second-order stochastic dominance. The necessary and sufficient condition for the infinite-order stochastic dominance portfolio efficiency is derived under the assumption of normality. The condition is used in the empirical part of the thesis where parametrical approach to the portfolio efficiency is compared to the nonparametric scenario approach. The derived necessary and sufficient condition is based on the assumption of normality; therefore we use two sets of data, one with fulfilled assumption of normality and the other for which the assumption of normality was unambigously rejected. Consequently, the influence of fulfillment of the normality assumption on the results of the necessary and sufficient condition for portfolio efficiency is estimated.
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Depth of two-dimensional data
Dočekalová, Denisa ; Šír, Zbyněk (advisor) ; Hlubinka, Daniel (referee)
In this paper we summarize the basic information about halfplane depth function. It consists of two parts. In the first part we deal with the halfplane depth based on the distribution function, we describe its basic properties and define the concepts of depth contours, central regions and the halfplane median. We also deal with these concepts in the rest of the paper with the main focus on the halfplane median. In the second part of this work we deal with the halfplane depth based on the random choice with the main focus on data visualization. The used methods for visualization are the display of depth contours and the bagplot. This work includes pictures of depth contours for specific distributions which were gained by implementation of an algorithm in the software Mathematica. 1
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Parametric estimation of GARCH model using MATLAB
Dúbravský, Martin ; Tran, Van Quang (advisor) ; Fučík, Vojtěch (referee)
Timely invariant variance is known not to be stylized fact of financial returns data. Motive of this bachelor thesis is to study financial data's typical variability of variance. In theoretical part, assumtions of GARCH models and its extensions, are summarized. GARCH family models' parameters are estimated, using maximum likelihood are estimated in empirical part. These models are estimated and evaluated across five assets, in which stock indicies DAX and SAP 500, FX major EURUSD and commodities natural gas and gold, are represented. In order to make assumptions about robabilistic distribution of data more realistic, not only Gaussian distribution, but also more leptokurtic Student's t-distribution is assumed to be present in data. Estimations are executed using software package MATLAB and EViews environment. For each asset, the best one of estimated GARCH models will be selected. Results suggest, that assumption of leptokurtic distribution generates models that describe volatility of studied assets better. Regarding testing for assymetric effects in volatility and estimation of EGARCH models, leverage effect of financial returns is shown to be present in returns of studied assets.
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Confidence Intervals for Quantiles
Horejšová, Markéta ; Kulich, Michal (advisor) ; Hlávka, Zdeněk (referee)
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are explained. Among nonparametric approaches, a special emphasis is dedicated to a recent method based on a multinomial distribution for calculating the overall confidence level of confidence intervals for all quantiles of interest using an efficient recursive algorithm, which is also described. Furthermore, a method based on Kolmogorov-Smirnov statistic or an asymptotic method using empirical distribution function and order statistics for quantile estimate are presented. A special parametric method for several quantiles of a normally distributed population is introduced along with a few of its modifications. Subsequently, a simulation is run to test the real coverage of the described theoretical methods. Powered by TCPDF (www.tcpdf.org)
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Shapiro-Wilk test of normality
Malíková, Kateřina ; Komárek, Arnošt (advisor) ; Zvára, Karel (referee)
In this work we introduce Shapiro-Wilk normality test testing examined statistical sampling. At first, we state the basic information about the normal distribution. Further, we describe the test and we derive the shape of the test statistic W and some of its analytical properties, including two moments and the maximum and minimum allowable values that it may take. We also find some approximations of various coefficients used for calculations and evaluation of the test and also the estimate of the distribution of the test statistics of Shapiro-Wilk test. In conclusion, we show an example of testing and method of implementation in computer programs.
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Multivariate Normal Distribution
Ježo, Jakub ; Kulich, Michal (advisor) ; Hlávka, Zdeněk (referee)
Title: Multivariate Normal Distribution Author: Jakub Ježo Department: Department of Probability and Mathematical Statistics Supervisor: doc. Mgr. Michal Kulich, Ph.D., Department of Probability and Mathematical Statistics Abstract: This bachelor thesis deals with the multivariate normal distribution, distributions derived from it and relations between them. The definition and characterization of the n-dimensional multinormal distribution, derivation of its characteristic function and definition of the matrix normal distribution are shown at the beginning. Further this thesis looks at the properties of the multivariate normal distribution and examines the linear combinations of normal vectors, li- near combinations of normal matrices and theirs properties. After that the qua- dratic forms of matrices from the normal distribution are shown, which leads to the Wishart distribution, its properties and the analysis of multidimensional data based on it. At the end of the thesis, the combinations of random vec- tors and matrix from the normal distribution are examined, which results to the Hotelling distribution and its properties. The distribution and properties of the sample mean vector and sample covariance matrix of a random sample from n- dimensional multinormal distribution are presented in this thesis....
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