Least squares estimator for regression models with some deterministic time varying parameters

被引：3

作者：

Boutahar, M

Deniau, C

机构：

[1] FAC SCI LUMINY,DEPT MATH,F-13288 MARSEILLE 09,FRANCE

[2] GREQAM VIEILLE CHARITE,F-13002 MARSEILLE,FRANCE

来源：

METRIKA | 1996年 / 43卷 / 01期

关键词：

martingale difference sequence; least squares; regression; rate of convergence;

D O I：

10.1007/BF02613897

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];

摘要：

Here we study the least squares estimates in some regression models. Fire assume that the evolution of the parameter is linearly explosive (i.e. polynomial), or stable (i.e. sinusoidal). We prove the strong consistency, and establish the rate of convergence.

引用

页码：57 / 67

页数：11

共 11 条

[1]

Boutahar M., 1991, STOCHASTICS STOCHAST, V37, P105

[2]

CHEN H. F., 1991, Identification and Stochastic Adaptive Control

[3]

TRICKS OR TREATS WITH THE HILBERT MATRIX [J].