ScholarGate
Assistent

Sammenlign metoder

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

BCa Bootstrap (Bias-korrigert og akselerert)×Bayesian Bootstrap (Rubin)×
FagfeltStatistikkStatistikk
FamilieRegression modelRegression model
Opprinnelsesår19871981
OpphavspersonBradley EfronRubin (1981); large-sample theory by Lo (1987)
TypeResampling confidence intervalResampling / posterior simulation
Opprinnelig kildeEfron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗
AliasBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence intervalBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap
Relaterte55
SammendragThe BCa bootstrap is a resampling method, introduced by Bradley Efron in 1987, that produces more accurate confidence intervals than the plain percentile bootstrap by applying a bias correction and an acceleration adjustment. It is recommended for skewed distributions and small samples.The Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated.
ScholarGateDatasett
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Download slides

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