Nonparametric Regression Tests Based on Least Squares
提出基于最小二乘残差平方和的半参数模型检验方法，在非参数部分施加光滑性条件以得到残差平方和的渐近正态性，可用于模型设定、变量显著性、光滑性和凹凸性检验，并允许异方差残差。
This paper proposes tests on semiparametric models based on the sum of squared residuals from a least-squares procedure. Smoothness conditions are imposed on the nonparametric portion of the model to obtain asymptotic normality of the sum of squared residuals. The approach yields tests of specification, significance, smoothness and concavity and allows for heteroskedastic residuals.