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Admissibility and Inadmissibility of an Estimate
 Vagner, Marcel ; Maciak, Matúš (advisor) ; Jurečková, Jana (referee)
The quality of a parameter estimate is usually assessed using the mean squared error (MSE). For one dimensional parameter, the estimate constructed using the least squares method is the best. However, for a vector parameter with more than two dimensions this estimator becomes inadmissible. There is always some different estimator which domi- nates the least squares estimate regardless of the parameter value. This phenomenon is well known as the Stein Paradox. The aim of this bachelor thesis is to describe admissi- bility and inadmissibility of an estimator, define the James-Stein estimator and perform a simulation study to compare different estimators. 1
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