ASYMPTOTIC ESTIMATION AND HYPOTHESIS TESTING RESULTS FOR VECTOR LINEAR TIME-SERIES MODELS

被引：37

作者：

KOHN, R

机构：

来源：

ECONOMETRICA | 1979年 / 47卷 / 04期

关键词：

D O I：

10.2307/1914144

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

For a general vector linear time series model the strong consistency and symptotic normality of parameter estimates obtained by maximizing a particular time domain approximation to a Gaussian likelihood is proved. To solve the normal equations a constrained Guass-Newton iteration is suggested. -Author

引用

页码：1005 / 1030

页数：26

共 28 条

[1] MAXIMUM LIKELIHOOD IDENTIFICATION OF GAUSSIAN AUTOREGRESSIVE MOVING AVERAGE MODELS [J].