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Бутстрап Инференција×Generalizovani metod najmanjih kvadrata (GLS)×
OblastStatistikaStatistika
PorodicaRegression modelRegression model
Godina nastanka19791935
TvoracBradley EfronAlexander Craig Aitken
TipResampling-based inferenceLinear estimator
Temeljni izvorEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Drugi nazivibootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap ÇıkarımıGLS, Aitken estimator, EGLS, feasible GLS
Srodne53
SažetakBootstrap 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.Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
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ScholarGateUporedite metode: Bootstrap Inference · Generalized Least Squares. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare