VARMA模型由於能描述變數間的相關性及動態結構，並能有效的預測時間數列的走勢，因此巳被廣泛地應用在各學科中。但由於VARMA模型中有參數數目極多及non-identifiable等問題，因此在統計推論上極為不易，至今仍無一套公認最佳的選模準則及推論方法。有鑑於此，本文回顧過去發展出的數種著名選模方法，逐一介紹，並提出可能的修正方式，期能找出更有效的選模方法。

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