一个半参数回归模型中Cramér渐近有效性的充要条件
A Sufficient and Necessary Condition on Cramér Asymptotic Efficiency in a Semiparametric Regression Model
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摘要: 本文考虑模型Y = Xrβ+ g（T）+ε,这里（Xr,T, Y）是k + 2-维随机向量,g是未知光滑函数,ε是均值为零方差有限的随机误差。本文证明了β的最小二乘估计是Cramér渐近有效的充要条件是误差ε服从正态分布N（0, σ2）。Abstract: The paper is concerned with the semiparametric regression model Y = Xrβ+ g（T）+ε, where（Xr,T, Y） are （k + 2）-dimensional random vector, g（·） is an unknown smooth function to be estimated, ε is variable error with zero mean and finite variance It is shown that the LS estimators of β is asymptotically efficiency in sense of Cramér if and only if ε-N（0, σ2）.
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