此篇論文主要在探討在時間序列中利用提出的Cross Validation (CV)方法選取選模準則，期望此方法能對於不同的資料選取到適用的選模準則，得到較佳的模型配適以及預測。模擬結果為當真實模型為AR無窮維度時，我們所提出的CV方法較為適用，但若真實模型為有限秩( finte order )時，則不適用。其中當真實模型之相關性較弱的時候，利用CVR(d)方法來當作選模準則較為恰當。在實例分析上，舉了兩個實例，實例一為台灣的出口物價指數，實例二為台灣台北、日月潭、恆春以及澎湖四地區之溫度變化觀察其結果。

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