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Estimating the error variance in nonparametric regression by a covariate-matched u-statistic
2003
Statistics (Berlin)
For nonparametric regression models with fixed and random design, two classes of estimators for the error variance have been introduced: second sample moments based on residuals from a nonparametric fit, and difference-based estimators. The former are asymptotically optimal but require estimating the regression function; the latter are simple but have larger asymptotic variance. For nonparametric regression models with random covariates, we introduce a class of estimators for the error variance
doi:10.1080/0233188031000078051
fatcat:dglomhvpmval7ekr7km7mb4cpq