ScholarGate
Asisten

Bandingkan metode

Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.

Diagnostik Pengaruh (Jarak Cook, DFFITS, Leverage)×Regresi Kuadrat Terkecil Biasa (Ordinary Least Squares - OLS)×
BidangStatistikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal19772019
PencetusR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Wooldridge (textbook treatment); classical least squares
TipeRegression diagnosticLinear regression
Sumber perintisCook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
AliasCook's distance, DFFITS, leverage, influential observation detectionordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Terkait55
RingkasanInfluence 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 1 Sumber
  3. PUBLISHED

Ke halaman pencarian Unduh salindia

ScholarGateBandingkan metode: Influence Diagnostics · OLS Regression. Diakses 2026-06-17 dari https://scholargate.app/id/compare