Browsing Faculty of Natural and Agricultural Sciences by Subject "Smooth function model"
Now showing items 1-2 of 2
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A nonparametric point estimation technique using the m-out-of-n bootstrap
(SASA, 2018)We investigate a method which can be used to improve an existing point estimator by a modification of the estimator and by using the m-out-of-n bootstrap. The estimation method used, known as bootstrap robust aggregating ... -
On the asymptotic theory of new bootstrap confidence bounds
(IMS, 2018)We propose a new method, based on sample splitting, for constructing bootstrap confidence bounds for a parameter appearing in the regular smooth function model. It has been demonstrated in the literature, for example, ...