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Model for short-term forecasting of photovoltaic energy production
Kotlorz, Lukáš ; Pelikán, Emil (advisor) ; Hlávka, Zdeněk (referee)
Nowadays, electricity production from photovoltaics power plants is becoming important increasingly. In order to set production to other power plants, it is necessary to predict the generation of electricity from these sources. The thesis is mainly devoted to models for short-term prediction, which is based on weather forecast. The models were designated by beta regression and linear regression with transformed explanatory variable. One part of thesis is devoted to Clear sky model, which is used to estimated the maximum possible production at given hour. 1
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Nonparametric regression estimators
Měsíček, Martin ; Hlávka, Zdeněk (advisor) ; Omelka, Marek (referee)
This thesis is focused on local polynomial smoothers of the conditional vari- ance function in a heteroscedastic nonparametric regression model. Both mean and variance functions are assumed to be smooth, but neither is assumed to be in a parametric family. The basic idea is to apply a local linear regression to squa- red residuals. This method, as we have shown, has high minimax efficiency and it is fully adaptive to the unknown conditional mean function. However, the local linear estimator may give negative values in finite samples which makes variance estimation impossible. Hence Xu and Phillips proposed a new variance estimator that is asymptotically equivalent to the local linear estimator for interior points but is guaranteed to be non-negative. We also established asymptotic results of both estimators for boundary points and proved better asymptotic behavior of the local linear estimator. That motivated us to propose a modification of the local li- near estimator that guarantees non-negativity. Finally, simulations are conducted to evaluate the finite sample performances of the mentioned estimators.
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Favoritism Under Social Pressure: Evidence From English Premier League
Herrmann, Vojtěch ; Večeř, Jan (advisor) ; Hlávka, Zdeněk (referee)
The aim of this thesis is to study the extent to which the English Premier League referees are influenced by social pressure, especially by the home support and by the general popularity of the teams. Using regression analysis, we compare the actual length of the overtime, which is fully in the competence of the referee, with the predicted one from the usual game stoppages. Then we try to identify factors that contribute to any possible discrepancy. Our results suggest that the games tend to be extended beyond the expectations when the outcome of the game still can change, i.e., when the score differential at the time 90:00 is either zero or one. However, this extra extension happens almost regardless of the playing teams and thus we find no evidence for referee bias towards any specific team. However, a small bias towards the group of "Big" teams has been found, but only in the games in which the score differential was different from one.
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Confidence bands for regression curves
Zavřelová, Adéla ; Hlávka, Zdeněk (advisor) ; Maciak, Matúš (referee)
This thesis deals with the constructions of the confidence band for a linear regression model. Basic characteristics of a linear model are given and constructions of different confidence bands are described for models, where the relationship is set by a one variable function. The main focus is on bands of polynomial models.
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Bayesian variable selection
Jančařík, Joel ; Komárek, Arnošt (advisor) ; Hlávka, Zdeněk (referee)
The selection of variables problem is ussual problem of statistical analysis. Solving this problem via Bayesian statistic become popular in 1990s. We re- view classical methods for bayesian variable selection methods and set a common framework for them. Indicator model selection methods and adaptive shrinkage methods for normal linear model are covered. Main benefit of this work is incorporating Bayesian theory and Markov Chain Monte Carlo theory (MCMC). All derivations needed for MCMC algorithms is provided. Afterward the methods are apllied on simulated and real data. 1
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Quantile curves
Michl, Marek ; Hlávka, Zdeněk (advisor) ; Hlubinka, Daniel (referee)
Modeling of quantile curves is a common problem across various fields in today's practice. The topic of this thesis is estimating quantile curves in case of two-sample gradual change. That is, when a relationship between two continuous variables in two samples is of interest, where the relationship is the same for both samples until a certain value of the explanatory variable. From that point on the relationship can differ. The result of this thesis is a procedure for estimating quantile curves, which fulfill this concept. 1
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Visual statistical inference
Jeliga, Jan ; Hlávka, Zdeněk (advisor) ; Maciak, Matúš (referee)
Graphs, and data visualization in general, play a important role in modern statistics. In this thesis, we address the possibility of using these for hypothesis testing. First, we introduce the concept of visual testing and define analogies for terms such as statistic or p-value and additionally we define the terms specific to visual testing. We demonstrate the method of visual testing on an example, where we parallelly perform a conventional test for the same data set and the same null and alternative hypothesis. Further, we inspect the possibility of use of Amazon Mechanical Turk for visual testing. We describe the design of visual test and present results of simulation experiments conducted in order to assess the power of the visual test and to compare it to conventional test. Powered by TCPDF (www.tcpdf.org)
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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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Tests of independence for multivariate data
Kudlík, Michal ; Omelka, Marek (advisor) ; Hlávka, Zdeněk (referee)
Title: Tests of independence for multivariate data Author: Bc. Michal Kudlík Department: Department of Probability and Mathematical Statistics Supervisor: Ing. Marek Omelka, PhD., Department of Probability and Mathema- tical Statistics Abstract: This thesis is an overview of tests of independence for multidimensi- onal data. The report includes tests on independence of categorical and conti- nuous random variables, tests assuming normal distribution of data, asymptotic nonparametric tests and permutation tests with application of the Monte Carlo method. This thesis shows the suitability of tests with properly chosen real data and checks significance level and compares the strength of the selected tests by simulation study while using appropriate statistical software. Based on the simu- lation study the thesis discusses an appropriateness of the use of different tests for different situations. Keywords: independence, permutation and asymptotic tests of independence, Monte Carlo method, simulation study 1
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Order statistics
Tělupil, Dominik ; Hlávka, Zdeněk (advisor) ; Jurečková, Jana (referee)
The aim of this work is to introduce general notions of theory of order statistics and the method of ranked set sampling (RSS). This statistical method is based on ranking of observed random variables which allows us to con- struct an unbiased estimator with lower variance than by using the method of sim- ple random sampling. In this work we will study estimators of the expected va- lue. Furthermore, we will investigate some properties of estimators based on RSS and some modifications of this method. The thesis contains a chapter about soft- ware simulations which verify the properties of estimators based on RSS. 1
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