National Repository of Grey Literature 158 records found  beginprevious83 - 92nextend  jump to record: Search took 0.01 seconds. 
Multiple comparison with controls
Sychova, Maryna ; Hlávka, Zdeněk (advisor) ; Komárek, Arnošt (referee)
The main theme of the diploma thesis is description of multiple comparison methods, which are used to compare pairs of means or medians. At the beggining we define multiple testing and describe methods that control the probability of first type error at level α. The Šidák method and the prerequi- sites required for its use are described in detail. The work also includes a brief description of analysis of variance and an overview of several methods of multiple comparison. Additionally, the method of multiple comparison with control, its modifications and practical implementation is presented.
Applications of bootstrap methods to time series
Baumová, Tereza ; Prášková, Zuzana (advisor) ; Hlávka, Zdeněk (referee)
Práce se vìnuje studiu variant metody bootstrap vhodných pro vy¹etøování vlastností autoregresních procesù s náhodnými koe cienty. Ètenáø je nejprve se- známen s pùvodní metodou bootstrap navr¾enou pro nezávislé stejnì rozdìlené náhodné velièiny a se základními variantami této metody bì¾nì pou¾ívanými pro analýzu èasových øad. Poté je pøedstaven autoregresní proces s náhodnými koe - cienty øádu p (RCA(p)). Jsou popsány základní vlastnosti tohoto procesu a blí¾e prozkoumány vlastnosti procesu RCA(1). V dal¹í èásti jsou uvedeny varianty me- tody bootstrap, které jsou v pøípadì procesu RCA(1) konzistentní, a pro metodu wild bootstrap je odvozena konzistence pro proces RCA(2). V poslední kapitole jsou na simulovaných datech ovìøeny vlastnosti popsaných metod. 1
Median in some statistical methods
Bejda, Přemysl ; Cipra, Tomáš (advisor) ; Hlávka, Zdeněk (referee) ; Víšek, Jan Ámos (referee)
Median in some statistical methods Abstract: This work is focused on utilization of robust properties of median. We propose variety of algorithms with respect to their breakdown point. In addition, other properties are studied such as consistency (strong or weak), equivariance and computational complexity. From practical point of view we are looking for methods balancing good robust properties and computational complexity, be- cause these two properties do not usually correspond to each other. The disser- tation is divided to two parts. In the first part, robust methods similar to the exponential smoothing are suggested. Firstly, the previous results for the exponential smoothing with ab- solute norm are generalized using the regression quantiles. Further, the method based on the classical sign test is introduced, which deals not only with outliers but also detects change points. In the second part we propose new estimators of location. These estimators select a robust set around the geometric median, enlarge it and compute the (iterative) weighted mean from it. In this way we obtain a robust estimator in the sense of the breakdown point which exploits more information from observations than standard estimators. We apply our approach on the concepts of boxplot and bagplot. We work in a general normed vector...
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
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.
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.
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.
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
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
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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