Consistency and Normality ofM-Estimators in Partly Linear Models with Stochastic Adapted Errors

DOI10.1080/03610926.2012.657329zbMath1319.62071OpenAlexW1966800325MaRDI QIDQ3168551

Li Yan, Xia Chen

Publication date: 31 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2012.657329

zbMATH Keywords

\(M\)-estimatorpiecewise polynomialpartly linear modelstochastic adapted sequence

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Robustness and adaptive procedures (parametric inference) (62F35)

Cites Work

• Unnamed Item
• Asymptotic normality of M-estimators in a semiparametric model with longitudinal data
• Strong limit theorems for arbitrary stochastic sequences
• Empirical likelihood inference for partial linear models under martingale difference sequence
• Consistency and normality of Huber-Dutter estimators for partial linear model
• Convergence rates for parametric components in a partly linear model
• Convergence of stopped sums of weakly dependent random variables
• A class of strong limit theorems for the sequences of arbitrary random variables.
• A limit theorem for partial sums of random variables and its applications.
• Optimal global rates of convergence for nonparametric regression
• Asymptotics of estimators in semi-parametric model under NA samples
• Estimation in a semiparametric model for longitudinal data with unspecified dependence structure
• A Note on the Convergent Rates of M-Estimates for a Partly Linear Model
• Robust Statistics

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