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On consistency for time series model selection

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  • William Kengne

    (THEMA, CY Cergy Paris Université)

Abstract

We consider the model selection problem for a large class of time series models, including, multivariate count processes, causal processes with exogenous covariates. A procedure based on a general penalized contrast is proposed. Some asymptotic results for weak and strong consistency are established. The non consistency issue is addressed, and a class of penalty term, that does not ensure consistency is provided. Examples of continuous valued and multivariate count autoregressive time series are considered.

Suggested Citation

  • William Kengne, 2023. "On consistency for time series model selection," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 437-458, July.
    • Handle: RePEc:spr:sistpr:v:26:y:2023:i:2:d:10.1007_s11203-022-09284-6
    DOI: 10.1007/s11203-022-09284-6
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    References listed on IDEAS

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