中文说明： 假定确定性函数 Y 具有加性高斯噪声，EVAR(Y) 返回这种噪声估计的方的差。 薄板样条平滑模型用来平滑 Y。它假设其广义的交叉验证分数是最小的模型可以提供的加性噪声方差。几个测试表明 EVAR 工作得很好"不太不规则"功能。
English Description：
Assuming that the deterministic function Y has additive Gaussian noise, EVAR(Y) returns an estimated variance of this noise. A thin-plate smoothing spline model is used to smooth Y. It is assumed that the model whose generalized cross-validation score is minimal can provide the variance of the additive noise. A few tests showed that EVAR works very well with "not too irregular" functions.