摘要
考虑回归模型，ｇ为Ｒ１上未知函数，β为ｐ×１维待估参数向量．本文基于模型的可加性得到了β和ｇ的估计量，证明了它们具有很好的大样本性质．
Consider the regression model Yi = Xi'β+g(ti) + ei for i=1, …,n. Here g is an unknown function on R1, β is a p×1 parameter vectors to be estimated and ei is an unobserved random error. In this paper, the additivity of the model is used to analyse the data, and the useful estimations and are established. It's shown that and have some nice properties.
出处
《应用数学学报》
CSCD
北大核心
1995年第3期353-363,共11页
Acta Mathematicae Applicatae Sinica
基金
国家自然科学基金
关键词
回归模型
最小二乘估计
半参数回归模型
Semiparametric model
additive regression
kernel weight function
least square estimation
