ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

윈저화 추정×영향력 진단 (쿡 거리, DFFITS, 레버리지)×
분야통계학통계학
계열Regression modelRegression model
기원 연도19601977
창시자Dixon (1960); robust estimation tradition (Wilcox)R. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)
유형Robust location/scale estimatorRegression diagnostic
원전Dixon, W. J. (1960). Simplified Estimation from Censored Normal Samples. Annals of Mathematical Statistics, 31(2), 385-391. DOI ↗Cook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗
별칭winsorization, winsorized mean, Winsorize Edilmiş TahminCook's distance, DFFITS, leverage, influential observation detection
관련55
요약Winsorized estimation is a robust technique that reduces the influence of outliers by clamping the extreme percentiles of a distribution to a chosen threshold. Introduced by Dixon (1960) and developed in the robust-estimation tradition of Wilcox, it keeps every observation in the sample rather than discarding any.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.
ScholarGate데이터셋
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Winsorized Estimation · Influence Diagnostics. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare