%0 Journal Article
%T STRONG CONSISTENCY OF ESTIMATORS IN PARTIAL LINEAR MODEL UNDER NA SAMPLES<br>NA样本部分线性模型估计的强相合性
%A ZHOU Xingcai
%A <br>周兴才
%A 胡舒合
%J 系统科学与数学
%D 2010
%I 
%X Consider the heteroscedastic regression model:$Y^{(j)}(x_{\rm in},t_{\rm in})=t_{\rm in}\beta+g(x_{\rm in})+\sigma_{\rm in}e^{(j)}(x_{\rm in}), 1\leq j\leq m, 1\leq i\leq n$, where $\sigma_{\rm in}^{2}=f(u_{\rm in})$, $(x_{\rm in},t_{\rm in},u_{\rm in})$ are fixed design points, $\beta$ is an unknown parameter, $g(\cdot)$ and $f(\cdot)$ are unknown functions, and the errors $\{e^{(j)}(x_{\rm in})\}$ are mean zero NA random variables. The strong consistency for least-squares estimator and weighted least-squares estimator of $\beta$ is studied based on the family of nonparametric estimates of $g(\cdot)$ and $f(\cdot)$.
%K Partial linear model
%K NA random variable
%K least-squares estimator
%K strong consistency<br>部分线性模型
%K NA变量
%K 最小二乘估计
%K 强相合性.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=0CD45CC5E994895A7F41A783D4235EC2&aid=F2C0F3FEC4AAA962EEF468EAAED7ADD2&yid=140ECF96957D60B2&vid=340AC2BF8E7AB4FD&iid=CA4FD0336C81A37A&sid=56C88B5AB58BAB20&eid=A68B4EE6F4C90B8C&journal_id=1000-0577&journal_name=系统科学与数学&referenced_num=0&reference_num=8