Multiple regression for single index model (日本計算機統計学会第16回シンポジウム) -- (特別セッション1 ポストゲノムと計算機統計)

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概要

• 論文の詳細を見る

• A simple method based on SIR (Sliced Inverse Regression) is proposed to explore an EDR vector for the single index model. We avoid the principle component analysis step of the original SIR by using two sample mean vectors in two slices of the response variable and their difference vector. The methodology can be effectively applied even when the number of covariates is large since it requires no matrix operation or iterative calculation.

• 日本計算機統計学会の論文
• 2002-10-31

著者

• Ohtaki Megu

  Hiroshima University

• Satoh Kenichi

  Hiroshima University

関連論文

• Multiple regression for single index model (日本計算機統計学会第16回シンポジウム) -- (特別セッション1 ポストゲノムと計算機統計)

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