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The confidence band of functions is complicated by the over-smoothing problem and the residual distribution. In this paper, we use bootstrap and data-sharpening methods to establish a general confidence band. The construction is simple and the band is narrower than existing estimation methods. At the same time, a technique based on quantiles makes the confidence band more controllable and damps down the stochastic error term. Afterwards, we conduct a limited simulation to illustrate that thedoi:10.6084/m9.figshare.12307577 fatcat:rt3v3od7bvbr3lg47d5mwwgchy