GENERAL TRIMMED ESTIMATION: ROBUST APPROACH TO NONLINEAR AND LIMITED DEPENDENT VARIABLE MODELS
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Publication:3551007
DOI10.1017/S0266466608080596zbMath1231.62026OpenAlexW3124780699MaRDI QIDQ3551007
Publication date: 8 April 2010
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s0266466608080596
Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) Order statistics; empirical distribution functions (62G30) General nonlinear regression (62J02)
Related Items (17)
Robustness of Bootstrap in Instrumental Variable Regression ⋮ Reweighted least trimmed squares: an alternative to one-step estimators ⋮ GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference ⋮ Robust diagnostics for the heteroscedastic regression model ⋮ \(\sqrt n\)-consistent robust integration-based estimation ⋮ Robust joint modeling of mean and dispersion through trimming ⋮ The least trimmed quantile regression ⋮ Semiparametrically weighted robust estimation of regression models ⋮ Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator ⋮ Semiparametric robust estimation of truncated and censored regression models ⋮ Moment condition tests for heavy tailed time series ⋮ Robust generalized empirical likelihood for heavy tailed autoregressions with conditionally heteroscedastic errors ⋮ TAIL AND NONTAIL MEMORY WITH APPLICATIONS TO EXTREME VALUE AND ROBUST STATISTICS ⋮ Testing for normality in linear regression models using regression and scale equivariant estimators ⋮ Robust estimation and inference for heavy tailed GARCH ⋮ Least tail-trimmed squares for infinite variance autoregressions ⋮ Generalized method of trimmed moments
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