1997-02-19Buch DOI: 10.18452/3806
Construction of Automatic Confidence Intervals in Nonparametric Heteroscedastic Regression by a Moment-Oriented Bootstrap
We construct pointwise confidence intervals for regression functions. The method uses nonparametric kernel estimates and the “moment-oriented” bootstrap method of Bunke which is a wild bootstrap based on smoothed local estimators of higher order error moments. We show that our bootstrap consistently estimates the distribution of mh(x0) - m(xo). In the present paper we focus on fully data-driven procedures and prove that the confidence intervals give asymptotically correct coverage probabilities.
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