ScholarGate
Асистент

Сравнение на методи

Прегледайте избраните методи един до друг; редовете с разлики са откроени.

Див бутстрап за регресионно заключение×Бутстрап извод×
ОбластСтатистикаСтатистика
СемействоRegression modelRegression model
Година на възникване19861979
СъздателWu (1986); refined by Davidson & Flachaire (2008)Bradley Efron
ТипResampling-based regression inferenceResampling-based inference
Основополагащ източникWu, 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 ↗
Други названияwild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrapbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Свързани55
РезюмеThe 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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: Wild Bootstrap · Bootstrap Inference. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare