National Repository of Grey Literature 103 records found  beginprevious56 - 65nextend  jump to record: Search took 0.00 seconds. 
Multidimensional statistics and applications to study genes
Bubelíny, Peter ; Klebanov, Lev (advisor) ; Jurečková, Jana (referee) ; Kalina, Jan (referee)
Title: Multidimensional statistics and applications to study genes Author: Mgr. Peter Bubelíny Department: Department of probability and mathematical statistics Supervisor: prof. Lev Klebanov, DrSc., KPMS MFF UK Abstract: Microarray data of gene expressions consist of thousands of genes and just some tens of observations. Moreover, genes are highly correlated between themselves and contain systematic errors. Hence the magnitude of these data does not afford us to estimate their correlation structure. In many statistical problems with microarray data, we have to test some thousands of hypotheses simultaneously. Due to dependence between genes, p-values of these hypotheses are dependent as well. In this work, we compared conve- nient multiple testing procedures reasonable for dependent hypotheses. The common manner to make microarray data more uncorrelated and partially eliminate systematic errors is normalizing them. We proposed some new normalizations and studied how different normalizations influence hypothe- ses testing. Moreover, we compared tests for finding differentially expressed genes or gene sets and identified some interesting properties of some tests such as bias of two-sample Kolmogorov-Smirnov test and interesting behav- ior of Hotelling's test for dependent components of observations. In the end of...
Political activity of Anselm of Canterbury
Kalina, Jan ; Suchánek, Drahomír (advisor) ; Drška, Václav (referee)
The thesis aims to describe Anselm's years as prior and abbot and his archiepiscopal career. Analyzing the years spent in the Norman monastery of Bec as a missionary and teacher in its school, the thesis notes the amount of knowledge and experiences which prepared Anselm for his archiepiscopal career. His intellectual qualities and theories are examined as well as some of his highly influential theological texts. Anselm also strove to spread the reforms of his teacher and mentor at Bec and his predecessor at Canterbury, Archbishop Lanfranc. Anselm's following archiepiscopal career spanned the reigns of two kings: William Rufus and Henry I. The study proves that the policies and attitudes of both rulers were quite different. Under the reign of William Rufus, Anselm tried to bring his ideal theoretical state of things into actuality, but the king resisted everything he attempted to do. With his death, Anselm's position changed rapidly and dramatically. Henry, on the other hand, excelled in the ability to work out a compromise. In the end, Anselm's archiepiscopal career concluded with cooperation between king and archbishop.
Tests of statistical hypotheses in measurement error models
Navrátil, Radim ; Jurečková, Jana (advisor) ; Hušková, Marie (referee) ; Kalina, Jan (referee)
The behavior of rank procedures in measurement error models was studied - if tests and estimates stay valid and applicable when there are some measurement errors involved and if not how to modify these procedures to be able to do some statistical inference. A new rank test for the slope parameter in regression model based on minimum distance esti- mator and an aligned rank test for an intercept were proposed. The (asymptotic) bias of R-estimator in measurement error model was also investigated. Besides measurement errors the problem of heteroscedastic model errors was considered - regression rank score tests of heteroscedasticity with nuisance regression and tests of regression with nuisance heterosce- dasticity were proposed. Finally, in location model tests and estimates of shift parameter for various measurement errors were studied. All the results were derived theoretically and then demonstrated numerically with examples or simulations.
Robust classification and discrimination
Rensová, Dita ; Kalina, Jan (advisor) ; Jonáš, Petr (referee)
This thesis is focused on classification methods and their robust alternatives. First, we recall the standard classification rules of linear and quadratic discrim- ination analysis. We also show some methods for estimating their probability of missclassification. Next we describe some existing robust multivariate estimators, their properties and computational algorithms. These estimators are consequently used to construct robust classification rules. Then, we describe the principal com- ponent analysis as a technique for dimension reduction. Again, we study methods for its robustification. Finally, we illustrate the usage of robust classification on both numerical simulations and real data. We also investigate the influence of the principal component analysis on classification results.
Robust Regression Estimators: A Comparison of Prediction Performance
Kalina, Jan ; Peštová, Barbora
Regression represents an important methodology for solving numerous tasks of applied econometrics. This paper is devoted to robust estimators of parameters of a linear regression model, which are preferable whenever the data contain or are believed to contain outlying measurements (outliers). While various robust regression estimators are nowadays available in standard statistical packages, the question remains how to choose the most suitable regression method for a particular data set. This paper aims at comparing various regression methods on various data sets. First, the prediction performance of common robust regression estimators are compared on a set of 24 real data sets from public repositories. Further, the results are used as input for a metalearning study over 9 selected features of individual data sets. On the whole, the least trimmed squares turns out to be superior to the least squares or M-estimators in the majority of the data sets, while the process of metalearning does not succeed in a reliable prediction of the most suitable estimator for a given data set.
Exact Inference In Robust Econometrics under Heteroscedasticity
Kalina, Jan ; Peštová, Barbora
The paper is devoted to the least weighted squares estimator, which is one of highly robust estimators for the linear regression model. Novel permutation tests of heteroscedasticity are proposed. Also the asymptotic behavior of the permutation test statistics of the Goldfeld-Quandt and Breusch-Pagan tests is investigated. A numerical experiment on real economic data is presented, which also shows how to perform a robust prediction model under heteroscedasticity. Theoretical results may be simply extended to the context of multivariate quantiles
Selection of Relevant Rules Within Clinical Decision Support
Kalina, Jan ; Zvárová, Jana
Clinical decision support systems represent important telemedicine tools with the ability to help physicians within the decision process leading to determining diagnosis, therapy or prognosis of patients. We proposed and implemented a prototype of a clinical decision support system, which has the form of an internet classification service. A specific property of this system is a sophisticated statistical component, which allows to handle also a large number of symptoms and signs. It namely optimizes the selection of such symptoms and signs which are the most relevant for determining the diagnosis. The performance of the prototype was verified on an analysis of gene expression data from a cardiovascular genetic study. The paper discusses principles of multivariate statistical thinking and reveals challenges of analyzing high-dimensional data with the number of observed variables (symptoms and signs) largely exceeding the number of observations (patients).
Testing heteroscedasticity
Špaková, Mária ; Kalina, Jan (advisor) ; Zichová, Jitka (referee)
Title: Testing heteroscedasticity Author: Mária Špaková Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Jan Kalina Ph.D., Institute of Computer Science, Academy of Sciences of the Czech Republic Abstract: This paper deals with testing heteroscedasticity. It is divided into four chapters. The first three chapters focus on the theory and the last one is devoted to practical testing using specific data. In the beginning of the theoretical part, basic concepts, knowledge and relationships concerning the linear regression, the regression model and the estimation of parameters by the method of ordinary least squares are introduced. The rest of this part is devoted to heteroskedasticity, its consequences and solutions. The following heteroscedasticity tests are being discussed: Breusch - Pagan, Goldfeld - Quandt and White. The practical part contains actual applications of the described tests and other methods to detect heteroskedasticity using three examples: Outlays vs. income, GDP and Expenditures on food. The aim of this paper is to discuss the above-mentioned tests. Three examples on real data with economic motivation confirm the theoretical properties of the tests. A uniformly optimal test of heteroscedasticity does not exist and different tests yield rather different...
Anabaptists in the Habsburg Monarchy
Kalina, Jan ; Županič, Jan (advisor) ; Suchánek, Drahomír (referee)
This thesis deals with history of the Anabaptist movement particularly in the first half of the 16th century. It describes religious and social life of the movement, including differences among particular Anabaptist communities. In individual chapters, special attention is devoted to communities in the Habsburg Monarchy, especially in the Czech lands. The text includes also brief biographies of important members of the movement.
Regression quantiles
Rusnák, Peter ; Kalina, Jan (advisor) ; Zvára, Karel (referee)
Title: Regression Quantiles Author: Peter Rusnák Department: Department of Probabilty and Mathematical Statistics Supervisor: RNDr. Jan Kalina, Ph.D.,Institute of Computer Science, AS CR Abstract: Quantile regression is a statistical method for specifying dependencies among variables, which was introduced by Koenker a Bassett in 1978. Since that time it has gone through a big development, when its theoretical properties have been under study, and it also has found many practical applications for data processing in variety of fields.While ordinary least-squares regression describes the relationship between one or more covariates X and the conditional mean of a response variable Y given X = x, quantile regression describes the relationship between X and the conditional quantiles of variable Y given X = x. This work contains the theory necessary for understanding relationship between standard and quantile regression and enabling include so received estimates to bigger group of M-estimates. The computation of coefficients for particular covariates is made by using Frisch-Newton algorithm belonging to methods of linear programming. The so-called regression ranks are also obtained as a by-product of this algorithm and we discuss their computational aspects and usage for hypothesis testing.In the second part, we...

National Repository of Grey Literature : 103 records found   beginprevious56 - 65nextend  jump to record:
See also: similar author names
70 KALINA, Jan
1 Kalina, J.
2 Kalina, Jakub
2 Kalina, Jaroslav
4 Kalina, Jiří
2 Kalina, Josef
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