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頁籤選單縮合
題 名 | Robustness Aspects of Model Choice |
---|---|
作 者 | Ronchetti,Elvezio; | 書刊名 | Statistica Sinica |
卷 期 | 7:2 1997.04[民86.04] |
頁 次 | 頁327-338 |
分類號 | 319.5 |
關鍵詞 | 模式選擇; Mallows's C抅; Robust C抅; Akaike criterion; Autoregressive models; Competing models; Crossvalidation; Diagnostics; Information theory; M-estimators; Nonnested hypotheses; Outliers; Robust Akaike criterion; Robust regression; Robust tests; Schwartz criterion; Time series; Variable selection; Weighted prediction error; |
語 文 | 英文(English) |
英文摘要 | Model selection is a key component in any statistical analysis. In this paper we discuss this issue from the point of view of robustness and we point out the extreme sensitivity of many classical model selection procedures to outliers and other departures from the distributional assumptions of the model. First, we focus on regression and review a robust version of Mallows's C[9064] as well as some related approaches. We then go beyond the regression model and discuss a robust version of the Akaike Information Criterion for general parametric models. |
本系統中英文摘要資訊取自各篇刊載內容。