Asymptotic confidence sets for the jump curve in bivariate regression problems
Asymptotic confidence sets for the jump curve in bivariate regression problems
复制标题
二元回归问题中跳跃曲线的渐近置信集
DOI:
10.1016/j.jmva.2019.02.017
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Holzmann
中科院分区:
文献类型:
--
作者:
Viktor;Eulert;Matthias;Holzmann
We construct uniform and point-wise asymptotic confidence sets for the single edge in an otherwise smooth image function which are based on rotated differences of two one-sided kernel estimators. Using methods from M-estimation, we show consistency of the estimators of location, slope and height of the edge function and develop a uniform linearization of the contrast process. The uniform confidence bands then rely on a Gaussian approximation of the score process together with anti-concentration results for suprema of Gaussian processes, while point-wise bands are based on asymptotic normality. The finite-sample performance of the point-wise proposed methods is investigated in a simulation study. An illustration to real-world image processing is also given.
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