Local \(M\)-estimation for conditional variance function with dependent data

DOI10.1216/RMJ-2016-46-1-333zbMath1338.62155OpenAlexW2397468128MaRDI QIDQ289728

Yunyan Wang, Mingtian Tang

Publication date: 31 May 2016

Published in: Rocky Mountain Journal of Mathematics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.rmjm/1464035867

zbMATH Keywords

robust estimationlocal linear regression\(\alpha \)-mixingconditional variance functionlocal \(M\)-estimator

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35)

Related Items (1)

Noise benefits to robust M-estimation of location in dependent observations

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Robust estimation for nonparametric generalized regression
• Volatility forecast comparison using imperfect volatility proxies
• Robust regression function estimation
• Nonparametric regression estimation under mixing conditions
• Conditional variance estimation in heteroscedastic regression models
• Local linear M-estimation for spatial processes in fixed-design models
• On a robust local estimator for the scale function in heteroscedastic nonparametric regression
• Asymptotic maximal deviation of M-smoothers
• Adaptive \(M\)-estimation in nonparametric regression
• M-estimation for autoregression with infinite variance
• Nonparametric curve estimation from time series
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Estimating continuous-time stochastic volatility models of the short-term interest rate
• Local polynomial estimators of the volatility function in nonparametric autoregression
• Nonlinear time series. Nonparametric and parametric methods
• Functional nonparametric model for time series: a fractal approach for dimension reduction
• Nonparametric conditional variance and error density estimation in regression models with dependent errors and predictors
• Variable bandwidth and one-step local \(M\)-estimator
• Robust estimates in generalized partially linear models
• Nonparametric functional data analysis. Theory and practice.
• On semiparametric \(M\)-estimation in single-index regression
• Asymptotic Normality for Regression Function Estimate Under Truncation and α-Mixing Conditions
• EMPIRICAL-LIKELIHOOD-BASED CONFIDENCE INTERVALS FOR CONDITIONAL VARIANCE IN HETEROSKEDASTIC REGRESSION MODELS
• An Effective Bandwidth Selector for Local Least Squares Regression
• Nonparametric estimation of the conditional variance function with correlated errors
• Locally modelled regression and functional data
• Efficient estimation of conditional variance functions in stochastic regression
• Local Polynomial Estimation of Regression Functions for Mixing Processes
• Local Polynomial Variance-Function Estimation
• Nonparametric estimation under long memory dependence
• The Relationship between Variable Selection and Data Agumentation and a Method for Prediction
• Regression with Nonstationary Volatility
• Signal-to-Noise Ratios, Performance Criteria, and Transformations

This page was built for publication: Local \(M\)-estimation for conditional variance function with dependent data