Controlling the significance levels of prediction error tests for linear regression models
控制线性回归模型预测误差检验的显著性水平
This paper provides evidence on problems associated with using standard tests for predictive failure when the errors of a linear regression model are not normally distributed. The ability of a simple bootstrap procedure to give a useful degree of control over the significance levels is examined.