Testing for coefficient stability of AR(1) model when the null is an integrated or a stationary process

研究成果: Article査読

6 被引用数 (Scopus)

抄録

In this paper, we propose a new test for coefficient stability of an AR(1) model against the random coefficient autoregressive model of order 1 neither assuming a stationary nor a non-stationary process under the null hypothesis of a constant coefficient. The proposed test is obtained as a modification of the locally best invariant (LBI) test by Lee [(1998). Coefficient constancy test in a random coefficient autoregressive model. J. Statist. Plann. Inference 74, 93-101]. We examine finite sample properties of the proposed test by Monte Carlo experiments comparing with other existing tests, in particular, the LBI test by McCabe and Tremayne [(1995). Testing a time series for difference stationary. Ann. Statist. 23 (3), 1015-1028], which is for the null of a unit root process against the alternative of a stochastic unit root process.

本文言語English
ページ(範囲)2731-2745
ページ数15
ジャーナルJournal of Statistical Planning and Inference
139
8
DOI
出版ステータスPublished - 2009 8 1
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 統計学、確率および不確実性
  • 応用数学

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