Semiparametric Estimates of the Relation Between Weather and Electricity Sales
用半参数回归方法估计电力销售与温度的非线性关系，允许数据线性变换，引入协变量和计费调整，并通过广义交叉验证选择平滑参数。
Abstract A nonlinear relationship between electricity sales and temperature is estimated using a semiparametric regression procedure that easily allows linear transformations of the data. This accommodates introduction of covariates, timing adjustments due to the actual billing schedules, and serial correlation. The procedure is an extension of smoothing splines with the smoothness parameter estimated from minimization of the generalized cross-validation criterion introduced by Craven and Wahba (1979). Estimates are presented for residential sales for four electric utilities and are compared with models that represent the weather using only heating and cooling degree days or with piecewise linear splines.