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Диагностика влияния (расстояние Кука, DFFITS, плечо)×Оценка на основе медианного абсолютного отклонения (MAD)×
ОбластьСтатистикаСтатистика
СемействоRegression modelRegression model
Год появления19771974
Автор методаR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Hampel (influence-curve treatment); classical robust statistics
ТипRegression diagnosticRobust scale estimator
Основополагающий источникCook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗
Другие названияCook's distance, DFFITS, leverage, influential observation detectionmedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
Связанные55
СводкаInfluence 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.Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Influence Diagnostics · MAD Estimation. Получено 2026-06-17 из https://scholargate.app/ru/compare