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Goodness-of-fit tests for vector autoregressive models in time series

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Abstract

The paper proposes and studies some diagnostic tools for checking the goodness-of-fit of general parametric vector autoregressive models in time series. The resulted tests are asymptotically chi-squared under the null hypothesis and can detect the alternatives converging to the null at a parametric rate. The tests involve weight functions, which provides us with the flexibility to choose scores for enhancing power performance, especially under directional alternatives. When the alternatives are not directional, we construct asymptotically distribution-free maximin tests for a large class of alternatives. A possibility to construct score-based omnibus tests is discussed when the alternative is saturated. The power performance is also investigated. In addition, when the sample size is small, a nonparametric Monte Carlo test approach for dependent data is proposed to improve the performance of the tests. The algorithm is easy to implement. Simulation studies and real applications are carried out for illustration.

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Authors and Affiliations

  1. College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, 310018, China

    JianHong Wu

  2. Department of Mathematics, Hong Kong Baptist University, Hong Kong, China

    LiXing Zhu

Authors
  1. JianHong Wu
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  2. LiXing Zhu
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Corresponding author

Correspondence to JianHong Wu.

Additional information

This work was supported by Research Grants Council of Hong Kong (Grant No. HKBU2-030/07P), Wu Jianhong was also supported by a grant from Humanities and Social Sciences in Chinese University (Grant No. 07JJD790154), Science Fund for Young Scholars of Zhejiang Gongshang University (Grant No. Q09-12) and Zhejiang Provincial Natural Science Foundation of China (Grant No. Y6090172).

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Wu, J., Zhu, L. Goodness-of-fit tests for vector autoregressive models in time series. Sci. China Ser. A-Math. 53, 187–202 (2010). https://doi.org/10.1007/s11425-009-0071-1

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  • DOI: https://doi.org/10.1007/s11425-009-0071-1

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