A Robust and Diagnostic Information Criterion for Selecting Regression Models
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- Atkinson Anthony C.
- Department of Statistics, London School of Economics
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- Riani Marco
- Dipartimento di Economia, Università di Parma
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We combine the selection of a statistical model with the robust parameter estimation and diagnostic properties of the Forward Search. As a result we obtain procedures that select the best model in the presence of outliers. We derive distributional properties of our method and illustrate it on data on ozone concentration. The effect of outliers on the choice of a model is revealed. Although our example is for regression, the connection with AIC is stressed.
収録刊行物
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- ＪＯＵＲＮＡＬ ＯＦ ＴＨＥ ＪＡＰＡＮ ＳＴＡＴＩＳＴＩＣＡＬ ＳＯＣＩＥＴＹ
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ＪＯＵＲＮＡＬ ＯＦ ＴＨＥ ＪＡＰＡＮ ＳＴＡＴＩＳＴＩＣＡＬ ＳＯＣＩＥＴＹ 38 (1), 3-14, 2008
日本統計学会
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詳細情報 詳細情報について
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- CRID
- 1390001205286431488
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- NII論文ID
- 110006835607
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- NII書誌ID
- AA1105098X
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- ISSN
- 13486365
- 18822754
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- MRID
- 2458313
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- NDL書誌ID
- 9598428
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可