摘要
对半参数模型Y_(ni)=β·t_(ni)+g(x_(ni))+ε_(ni),(1≤i≤n),利用一般权函数并综合最小二乘法,定义了β,g的估计量β_n,g_n.在误差为线性过程时,获得了β_n和g_n的r阶矩相合性及g_n的渐进正态性.
Considering semiparametric regression model with a linear process errors Ynt=β·tni＋g（xni）＋εni,1≤i≤n, we use the least squares and usual weighted method to define the estimates βn and gn for β and g and obtain their r-th mean consistency and asymptotic normality for gn under suitable conditions.
出处
《纯粹数学与应用数学》
CSCD
2010年第1期171-176,共6页
Pure and Applied Mathematics
基金
国家自然科学基金(5084602)
陕西省教育厅专项科研计划基金(03JK059)
关键词
半参数回归模型
线性过程
r阶矩相合性
渐进正态性
semiparametric regression model, linear process sequence, r-th mean consistency, asymptotic normality.
