ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Wild Bootstrap for Regression Inference×Bootstrap-inferens×
FagfeltStatistikkStatistikk
FamilieRegression modelRegression model
Opprinnelsesår19861979
OpphavspersonWu (1986); refined by Davidson & Flachaire (2008)Bradley Efron
TypeResampling-based regression inferenceResampling-based inference
Opprinnelig kildeWu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI ↗Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗
Aliaswild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrapbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Relaterte55
SammendragThe wild bootstrap is a resampling method for regression models with heteroscedastic errors, introduced by Wu (1986) and refined by Davidson and Flachaire (2008). It builds a bootstrap distribution by rescaling each fitted residual with a random sign, so that standard errors and confidence intervals stay valid when the error variance is not constant or the data are clustered.Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.
ScholarGateDatasett
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Download slides

ScholarGateSammenlign metoder: Wild Bootstrap · Bootstrap Inference. Hentet 2026-06-15 fra https://scholargate.app/no/compare