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Nonlinear time series contiguous to AR(1) processes and a related efficient test for linearity

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  • Hwang, Sun Y.
  • Basawa, I. V.

Abstract

A class of nonlinear time series models contiguous to a first-order autoregressive process (AR(1)) is introduced. The local asymptotic normality of the log-likelihood ratio statistic for testing for linearity is established. An efficient test of linearity is then obtained and its asymptotic power function is derived. An extension to autoregressive conditionally heteroscedastic contiguous alternative models to AR(1) is also discussed and an efficient test of linearity is derived for this class also.

Suggested Citation

  • Hwang, Sun Y. & Basawa, I. V., 2001. "Nonlinear time series contiguous to AR(1) processes and a related efficient test for linearity," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 381-390, May.
    • Handle: RePEc:eee:stapro:v:52:y:2001:i:4:p:381-390
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    6. Paul D. Feigin & Richard L. Tweedie, 1985. "Random Coefficient Autoregressive Processes:A Markov Chain Analysis Of Stationarity And Finiteness Of Moments," Journal of Time Series Analysis, Wiley Blackwell, vol. 6(1), pages 1-14, January.
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    Cited by:

    1. Laïb, Naâmane & Lounis, Tewfik, 2021. "Asymptotically optimal tests for non-linear autoregressive model with β-ARCH errors," Statistics & Probability Letters, Elsevier, vol. 178(C).

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