非参数回归函数混合型估计的均方收敛性
MEAN SQUARE CONVERGENCY OF A MIXING-TYPE ESTIMATION OF NONPARAMETRIC REGRESSION FUNCTION
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摘要: Stone提出了用权函数法与最小二乘法结合起来估计回归函数m(x)=E(Y|X)的方法并研究了估计的弱相合性;赵江研究了这种估计的均方相合性,其中要求E|Y|8d+8<∞。本文给出一种改进的混合型估计,在只要求EY2<∞且其它条件与2相同的情形下证明了改进估计的均方相合性。Abstract: Stone proposed a method of estimating the regression function m(X)=E(Y|X) by combining the classical LS estimation and the nonparametric weight-function estimation and established the weak consistency of the estimation. Zhao Jiang proved the mean square consistency of the estimation under E|Y|8d+8<∞ and other conditions. This paper gives an improved estimation of m(X). We show that our estimation is of mean square consistency under EY2<∞ and the same other condition as 2.