On sufficient conditions for the strong consistency of least-squares estimates

被引：0

作者：

da Silva, Joao Lita ^{[1
,2
]}

机构：

[1] Univ Nova Lisboa, Fac Sci & Technol, Dept Math, P-2829516 Quinta Da Torre, Caparica, Portugal

[2] Univ Nova Lisboa, Fac Sci & Technol, CMA, P-2829516 Quinta Da Torre, Caparica, Portugal

来源：

STATISTICS | 2014年 / 48卷 / 03期

关键词：

strong consistency; regression models; least-squares estimates; 60F15; REGRESSION-MODELS;

D O I：

10.1080/02331888.2012.760096

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The strong consistency of the least-squares estimates in regression models is obtained when the errors are i.i.d. with absolute moment of order r, 0 < r <= 2. The assumptions presented for the random error sequence will permit us to obtain improvements of the conditions on the regressors in order to obtain the strong consistency of the least-squares estimates in linear and nonlinear regression models.

引用

页码：657 / 667

页数：11

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