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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Detekce změn v lineárních modelech a bootstrap
 Čellár, Matúš ; Prášková, Zuzana (advisor) ; Hušková, Marie (referee)
This thesis discusses the changes in parameters of linear models and methods of their detection. It begins with a short introduction of the two basic types of change point detection procedures and bootstrap algorithms developed specifically to deal with dependent data. In the following chapter we focus on the location model - the simplest example of a linear model with a change in parameters. On this model we will illustrate a way of long-run variance estimation and implementation of selected bootstrap procedures. In the last chapter we show how to extend the applied methods to linear models with a change in parameters. We will compare the performance of change point tests based on asymptotic and bootstrap critical values through simulation studies in both our considered methods. The performance of selected long-run variance estimator will also be examined both for situations when the change in parameters occurs and when it does not. 1
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Detekce změn v lineárních modelech a bootstrap
 Čellár, Matúš ; Prášková, Zuzana (advisor) ; Hušková, Marie (referee)
This thesis discusses the changes in parameters of linear models and methods of their detection. It begins with a short introduction of the two basic types of change point detection procedures and bootstrap algorithms developed specifically to deal with dependent data. In the following chapter we focus on the location model - the simplest example of a linear model with a change in parameters. On this model we will illustrate a way of long-run variance estimation and implementation of selected bootstrap procedures. In the last chapter we show how to extend the applied methods to linear models with a change in parameters. We will compare the performance of change point tests based on asymptotic and bootstrap critical values through simulation studies in both our considered methods. The performance of selected long-run variance estimator will also be examined both for situations when the change in parameters occurs and when it does not. 1
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Conditional distributions and condeitional expectations
 Čellár, Matúš ; Hlubinka, Daniel (advisor) ; Janák, Josef (referee)
This paper discusses conditional distributions and conditional expectations, their introduction and basic properties. We begin with the definition of conditional probability, show a few theorems and demonstrate their application on an example. From there we move on to the conditioning with respect to random events and discrete random variables. In the general case we help ourselves with the definition of conditional expectation as random variable, show its properties, ways of expression and the fact that the introduction in the discrete case does not lead to a contradiction with the general definition. Then we deduce the criteria that have to be met for the conditional distribution to exist and in the last part we solve a number of theoretical problems.
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