VECTOR LINEAR TIME SERIES MODELS

被引：150

作者：

DUNSMUIR, W ^{[1
]}

HANNAN, EJ ^{[1
]}

机构：

[1] Australian Natl Univ, Canberra, ACT 2600, AUSTRALIA

来源：

ADVANCES IN APPLIED PROBABILITY | 1976年 / 8卷 / 02期

关键词：

LINEAR PROCESSES; VECTOR ARMA MODELS; IDENTIFICATION; LIMIT THEOREMS; MARTINGALES; FOURIER METHODS;

D O I：

10.2307/1425908

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：

This paper presents proofs of the strong law of large numbers and the central limit theorem for estimators of the parameters in quite general finite-parameter linear models for vector time series. The estimators are derived from a Gaussian likelihood (although Gaussianity is not assumed) and certain spectral approximations to this. An important example of finite-parameter models for multiple time series is the class of autoregressive moving-average (ARMA) models and a general treatment is given for this case. This includes a discussion of the problems associated with identification in such models.

引用

页码：339 / 364

页数：26

共 21 条

[1]

AUSLANDER L, 1963, INTRO DIFFERNTIABLE

[2]

Billingsley P., 1961, P AM MATH SOC, V12, P788

[3] EXPONENTIAL MODEL FOR SPECTRUM OF A SCALAR TIME SERIES [J].