Asymptotic behavior of the empiric distribution of M-estimated residuals from a regression model with many parameters
From MaRDI portal
Publication:1088338
DOI10.1214/aos/1176350056zbMath0612.62072OpenAlexW2075922005MaRDI QIDQ1088338
Publication date: 1986
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1176350056
asymptoticsGaussian processkernelempirical distributionM-estimatorgeneral linear modelasymptotic behavior of residualstightness result
Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)
Related Items (27)
Asymptotic properties of hazard rate estimator in censored linear regression ⋮ A law of the iterated logarithm for error density estimator in censored linear regression ⋮ Estimating functionals of the error distribution in parametric and nonparametric regression ⋮ Empirical process of residuals for high-dimensional linear models ⋮ Some results on generalized regression quantiles ⋮ A bootstrap version of the residual-based smooth empirical distribution function ⋮ Weak and strong uniform consistency of a kernel error density estimator in nonparametric regression ⋮ Estimating the error distribution function in semiparametric additive regression models ⋮ Maximum deviation of error density estimators in censored linear regression ⋮ Correcting MM estimates for ``fat data sets ⋮ Critical dimension in profile semiparametric estimation ⋮ Smooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression Residuals ⋮ On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property ⋮ On the impact of predictor geometry on the performance on high-dimensional ridge-regularized generalized robust regression estimators ⋮ Can we trust the bootstrap in high-dimension? ⋮ Asymptotic distributions of error density and distribution function estimators in nonparametric regression ⋮ The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled Chi-square ⋮ Hypothesis testing in linear regression when \(k/n\) is large ⋮ Asymptotic Properties of Error Density Estimator in Regression Model Under α-Mixing Assumptions ⋮ Estimating the innovation distribution in nonparametric autoregression ⋮ Empirical process based on the recursive residuals in functional measurement error models ⋮ Testing goodness of fit for the distribution of errors in multivariate linear models ⋮ Asymptotic normality of posterior distributions for exponential families when the number of parameters tends to infinity. ⋮ Comment ⋮ Weak convergence of the empirical process of residuals in linear models with many parameters ⋮ Another look at the jackknife: Further examples of generalized bootstrap ⋮ Consistency of error density and distribution function estimators in nonparametric regression.
This page was built for publication: Asymptotic behavior of the empiric distribution of M-estimated residuals from a regression model with many parameters
