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BCa Bootstrap (Sesgado y Acelerado Corregido)×Inferencia Bootstrap×
CampoEstadísticaEstadística
FamiliaRegression modelRegression model
Año de origen19871979
Autor originalBradley EfronBradley Efron
TipoResampling confidence intervalResampling-based inference
Fuente seminalEfron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗
AliasBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence intervalbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Relacionados55
ResumenThe 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.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.
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ScholarGateComparar métodos: BCa Bootstrap · Bootstrap Inference. Recuperado el 2026-06-15 de https://scholargate.app/es/compare