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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Goodness of fit tests with nuisance parameters
 Baňasová, Barbora ; Hušková, Marie (advisor) ; Hlávka, Zdeněk (referee)
This thesis deals with the goodness of fit tests in nonparametric model in the presence of unknown parameters of the probability distribution. The first part is devoted to understanding of the theoretical basis. We compare two methodologies for the construction of test statistics with application of empirical characteristic and empirical distribution functions. We use kernel estimates of regression functions and parametric bootstrap method to approximate the critical values of the tests. In the second part of the thesis, the work is complemented with the simulation study for different choices of weighting functions and parameters. Finally we illustrate the use and the comparison of goodness of fit tests on the example with the real data set. Powered by TCPDF (www.tcpdf.org)
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Parameter estimation based on estimated data
 Lachout, Petr
Linear regression model containing nuisance parameters is considered. Stability of estimators derived by OLS- or M-estimation procedure is treated while the nuisance parameters are replaced by their estimation.
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