ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

ロバスト因子分析×影響診断(Cook距離、DFFITS、レバレッジ)×
分野統計学統計学
系統Regression modelRegression model
提唱年20031977
提唱者Pison, Rousseeuw, Filzmoser & CrouxR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
種類Robust latent-factor modelRegression diagnostic
原典Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145-172. DOI ↗Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗
別名robust factor analysis, outlier-resistant factor analysis, MCD-based factor analysis, Robust Faktör AnaliziCook's distance, DFFITS, leverage, influential observation detection
関連55
概要Robust Factor Analysis recovers the latent factor structure of multivariate continuous data while resisting the distorting pull of outliers. Introduced by Pison, Rousseeuw, Filzmoser and Croux (2003), it replaces the classical sample covariance with a robust estimator such as the Minimum Covariance Determinant (MCD) or an S-estimator before extracting factors.Influence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Robust Factor Analysis · Influence Diagnostics. 2026-06-15に以下より取得 https://scholargate.app/ja/compare