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Робастный факторный анализ×Диагностика влияния (расстояние Кука, DFFITS, плечо)×
ОбластьСтатистикаСтатистика
СемействоRegression modelRegression model
Год появления20031977
Автор методаPison, Rousseeuw, Filzmoser & CrouxR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
ТипRobust latent-factor modelRegression diagnostic
Основополагающий источникPison, 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 ↗
Другие названияrobust factor analysis, outlier-resistant factor analysis, MCD-based factor analysis, Robust Faktör AnaliziCook's distance, DFFITS, leverage, influential observation detection
Связанные55
СводкаRobust 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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Robust Factor Analysis · Influence Diagnostics. Получено 2026-06-15 из https://scholargate.app/ru/compare