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Profile likelihood
 Pejřimovský, Pavel ; Omelka, Marek (advisor) ; Jurečková, Jana (referee)
This thesis deals with a statistical method called pro le likelihood. We use it in estimating the unknown parameters in the presence of interfering parameters, compiling con dence intervals or testing hypotheses for example. Pro le likelihood is directly derived from the maximum likelihood method, which is one of the fundamental methods of mathematical statistics in estimating the unknown parameters. The maximum likelihood method is the base for asymptotic tests and their possible generalization on tests with nuisance parameters. In this work we show that there is some connection between the pro le likelihood and tests with nuisance parameters . It also illustrates the usage pro le credibility of the classic examples of the normal distribution. Powered by TCPDF (www.tcpdf.org)
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