Optimal test for PAR(1) dependence against PSETAR(2,1,1) models with specified threshold

被引：1

作者：

Merzougui, M. ^{[1
]}

机构：

[1] Univ Badji Mokhtar, Dept Math, Annaba, Algeria

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2016年 / 45卷 / 04期

关键词：

Local asymptotic "most stringent" test; Local asymptotic normality; Periodic autoregressive; Periodic self-exciting threshold autoregressive; 62F12; 62M10; AUTOREGRESSIVE TIME-SERIES; ASYMPTOTIC-DISTRIBUTION; ADAPTIVE ESTIMATION; ARMA PROCESSES; TREND;

D O I：

10.1080/03610926.2013.853788

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 is devoted to testing a classical periodic autoregressive against a periodic threshold autoregressive model with specified threshold. The local asymptotic normality property is shown via the adapted sufficient conditions due to Swensen (1985). Using this result we consider the case where the innovation density is specified, and we obtain a parametric local asymptotic most stringent test.

引用

页码：872 / 886

页数：15

共 26 条

[1] Locally asymptotically optimal tests for AR(p) against diagonal bilinear dependence [J].