ScholarGate
Asistente

Comparar métodos

Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.

Diagnóstico de influencia (distancia de Cook, DFFITS, apalancamiento)×Estimación por Desviación Absoluta Mediana (MAD)×
CampoEstadísticaEstadística
FamiliaRegression modelRegression model
Año de origen19771974
Autor originalR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Hampel (influence-curve treatment); classical robust statistics
TipoRegression diagnosticRobust scale estimator
Fuente seminalCook, 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 ↗
AliasCook's distance, DFFITS, leverage, influential observation detectionmedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
Relacionados55
ResumenInfluence 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.
ScholarGateConjunto de datos
  1. v1
  2. 2 Fuentes
  3. PUBLISHED
  1. v1
  2. 2 Fuentes
  3. PUBLISHED

Ir a la búsqueda Descargar diapositivas

ScholarGateComparar métodos: Influence Diagnostics · MAD Estimation. Recuperado el 2026-06-17 de https://scholargate.app/es/compare