一个部份自回归模型的渐近有效性<英>  

Asymptotic Efficiency in a Partly Autoregressive Model

作　　者：粱华[1] 

机构地区：[1]中国科学院系统科学研究所

出　　处：《应用概率统计》1995年第3期235-246,共12页Chinese Journal of Applied Probability and Statistics

摘　　要：本文考虑部分自回归模型Ｘｔ＝ｘｔ－１β＋ｇ（Ｕｔ）＋εｔ，ｔ≥１。这里ｇ是一未知函数，β是和待估参数，εｊ是具有０均值和方差σ＾２的ｉ．ｉ．ｄ．误差，Ｕｔｉ．ｉ．ｄ．服从［０，１］上均匀分布。Consider the model X_t = X_(t-1)β + g(l't) + ε_i for t≥ 1. Here g is an unknown function, β is an unknown parameter to be estimated and ε_j are i.i d. with mean 0 and variance σ~2 and U_t are i.i.d. random variables obeyed uniformly on {0, l} The order of convergence of consistent estimators and the bound of asymptotic efficiency in sense of Takeuchi are given. Meanwhile we give a necessary and sufficient condition that the least squares of β is asymptotically efficient, and we also show that the MLE is asymptotically efficient.

关 键 词：渐近有效性 部分自回归模型 回归 MLE 

分 类 号：O212.1[理学—概率论与数理统计]