parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical doublebootstrap procedure with the same number of samples.
Andreea L. Erciulescu,
Wayne A. Fuller
Statistics in Transition New Series, Volume 17 , ISSUE 1, 9–24
In the paper selected nonparametric and semiparametric estimation methods of higher orders quantiles are considered. The construction of nonparametric confidence intervals is based on order statistics of appropriate ranks from random samples or from generated bootstrap samples. Semiparametric bootstrap methods are characterized by doublebootstrap simulations. The values of bootstrap sample below the prearranged threshold are generated by the empirical distribution and the values above this
Statistics in Transition New Series, Volume 17 , ISSUE 4, 737–748
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