Asymptotic Behavior of a Class of Confidence Regions Based on Ranks in Regression
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Publication:5618835
DOI10.1214/aoms/1177693398zbMath0215.54204OpenAlexW2051112332MaRDI QIDQ5618835
Publication date: 1971
Published in: The Annals of Mathematical Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aoms/1177693398
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On the asymptotic normality of the R-estimators of the slope parameters of simple linear regression models with associated errors ⋮ Unnamed Item ⋮ Center-Outward R-Estimation for Semiparametric VARMA Models ⋮ Estimation in autoregressivemodels based on autoregressionrank scores ⋮ Generalized R-estimators under conditional heteroscedasticity ⋮ Semiparametrically efficient rank-based inference for shape. II: Optimal \(R\)-estimation of shape ⋮ R-estimation for arma models ⋮ Asymmetric Errors in Linear Models: Estimation—Theory and Monte Carlo ⋮ Optimal, fixed length, nonparametric sequential confidence limits for a translation parameter ⋮ One-step R-estimation in linear models with stable errors ⋮ A weighted dispersion function for estimation in linear models ⋮ On general notions of depth for regression ⋮ Asymptotic optimality of Hodges-Lehmann inverse rank likelihood estimators ⋮ Estimation in a linear model based on regression rank scores ⋮ Finite-sample generalized confidence distributions and sign-based robust estimators in median regressions with heterogeneous dependent errors ⋮ R-estimation in autoregression with square-integrable score function
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