Large sample properties of parameter estimates for periodic ARMA models

被引：75

作者：

Basawa, IV ^{[1
]}

Lund, R ^{[1
]}

机构：

[1] Univ Georgia, Athens, GA 30602 USA

来源：

JOURNAL OF TIME SERIES ANALYSIS | 2001年 / 22卷 / 06期

关键词：

least squares; maximum likelihood; periodic time series; PARMA model; ARMA model; VARMA model;

D O I：

10.1111/1467-9892.00246

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper studies the asymptotic properties of parameter estimates for causal and invertible periodic autoregressive moving-average (PARMA) time series models. A general limit result for PARMA parameter estimates with a moving-average component is derived. The paper presents examples that explicitly identify the limiting covariance matrix for parameter estimates from a general periodic autoregression (PAR), a first-order periodic moving average (PMA(1)), and the mixed PARMA(1,1) model. Some comparisons and contrasts to univariate and vector autoregressive moving-average sequences are made.

引用

页码：651 / 663

页数：13

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