Empirical process of residuals for high-dimensional linear models

From MaRDI portal
Publication:1922408

DOI10.1214/aos/1033066211zbMath0853.62042OpenAlexW2079087363MaRDI QIDQ1922408

Enno Mammen

Publication date: 7 January 1997

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1033066211




Related Items

Asymptotic properties of hazard rate estimator in censored linear regressionEstimating robot strengths with application to selection of alliance members in FIRST robotics competitionsParametric copula adjusted for non- and semiparametric regressionRidge regression revisited: debiasing, thresholding and bootstrapA law of the iterated logarithm for error density estimator in censored linear regressionEstimating functionals of the error distribution in parametric and nonparametric regressionConditional predictive inference for stable algorithmsCopula-based tests for cross-sectional independence in panel modelsTesting stochastic dominance with many conditioning variablesA bootstrap version of the residual-based smooth empirical distribution functionModels as approximations. I. Consequences illustrated with linear regressionEstimating linear functionals of the error distribution in nonparametric regressionWeak and strong uniform consistency of a kernel error density estimator in nonparametric regressionEstimating the error distribution function in semiparametric additive regression modelsMaximum deviation of error density estimators in censored linear regressionCorrecting MM estimates for ``fat data setsCritical dimension in profile semiparametric estimationSmooth Residual Bootstrap for Empirical Processes of Non‐parametric Regression ResidualsOn the residual empirical process based on the ALASSO in high dimensions and its functional oracle propertyResidual bootstrap tests in linear models with many regressorsInference for conditional value-at-risk of a predictive regressionAsymptotic distributions of error density and distribution function estimators in nonparametric regressionHypothesis testing in linear regression when \(k/n\) is largeAsymptotic Properties of Error Density Estimator in Regression Model Under α-Mixing AssumptionsEstimating the innovation distribution in nonparametric autoregressionTesting goodness of fit for the distribution of errors in multivariate linear modelsApplied regression analysis bibliography update 1994-97CommentWeak convergence of the empirical process of residuals in linear models with many parametersGoodness-of-fit tests for mixed model diagnostics.Consistency of error density and distribution function estimators in nonparametric regression.



Cites Work