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Diagnostic checking of multivariate nonlinear time series models with martingale difference errors

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  • Chabot-Hallé, Dominique
  • Duchesne, Pierre

Abstract

In this article, we derive the asymptotic distribution of residual autocovariance and autocorrelation matrices for a general class of multivariate nonlinear time series models by assuming only that the error term is a martingale difference sequence. Two types of applications are developed: global test statistics of the portmanteau type and one-lag test statistics, which describe the residual correlation at individual lags. To illustrate the proposed methodology, simulation results are reported for diagnosing multivariate threshold time series models. The following test statistics are compared: the classical test statistics presuming independent errors and the proposed methodology which supposes only martingale difference errors.

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  • Chabot-Hallé, Dominique & Duchesne, Pierre, 2008. "Diagnostic checking of multivariate nonlinear time series models with martingale difference errors," Statistics & Probability Letters, Elsevier, vol. 78(8), pages 997-1005, June.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:8:p:997-1005
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    Cited by:

    1. Boubacar Maïnassara, Yacouba & Raïssi, Hamdi, 2015. "Semi-strong linearity testing in linear models with dependent but uncorrelated errors," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 110-115.
    2. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    3. De Gooijer, Jan G., 2023. "On portmanteau-type tests for nonlinear multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    4. Boubacar Mainassara, Yacouba, 2009. "Multivariate portmanteau test for structural VARMA models with uncorrelated but non-independent error terms," MPRA Paper 18990, University Library of Munich, Germany.
    5. Li, Muyi & Zhang, Yanfen, 2022. "Bootstrapping multivariate portmanteau tests for vector autoregressive models with weak assumptions on errors," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).

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