Bahadur-Kiefer representations for GM-estimators in autoregression models

DOI10.1016/0304-4149(95)00008-UzbMath0817.62077OpenAlexW2083373394MaRDI QIDQ1890719

Zhiwei Zhu, Hira L. Koul

Publication date: 23 May 1995

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(95)00008-u

zbMATH Keywords

rate of convergenceleast absolute deviationstrong consistencyautoregressionscore functionleast squareFreedman inequalitygeneralized \(M\)-estimatorsBahadur-Kiefer type representationsHuber \((k)\) estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

Strong convergence of estimators in nonlinear autoregressive models, Glivenko-Cantelli theorem for the kernel error distribution estimator in the first-order autoregressive model, Robust estimation of nonlinear regression with autoregressive errors., Robust goodness-of-fit tests for \(\text{AR} (p)\) models based on \(L_1\)-norm fitting

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