Abstract
The empirical process, where unknown parameters of the underlying distribution function are estimated by bootstrap methods, is considered. It is approximated by a sequence of Gaussian process. In the maximum likelihood estimation case it converges to a Brownian Bridge. The asymptotic distribution of Cramér-von Mises, Anderson-Darling and Kolmogorov-Smirnov test statistics are derived.
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