Average-Width Optimality for Confidence Bands in Simple Linear Regression
研究了在整个实数线上构建简单线性回归最优置信带的问题，以加权平均宽度最小化为最优准则，并比较了双曲线带和分段线带的性能。
Abstract The problem of constructing optimal confidence bands for a simple linear regression over the whole real line is considered. Optimality is defined as minimization of the average width of the bands weighted by a normalized function. This weight function is presented as an indicator of experimental interest in the varying width of the band. A comparison between the commonly seen hyperbolic bands and segmented-line bands is presented. Key Words: Simultaneous confidence intervalsPrior weight functionsConstrained minimization