Nonparametric conditional variance and error density estimation in regression models with dependent errors and predictors
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Publication:1952211
DOI10.1214/11-EJS629zbMath1274.62244MaRDI QIDQ1952211
Cornelia Wichelhaus, Rafał Kulik
Publication date: 28 May 2013
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.ejs/1314018118
Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)
Related Items (12)
Smooth Estimation of Error Distribution in Nonparametric Regression Under Long Memory ⋮ Local \(M\)-estimation for conditional variance function with dependent data ⋮ Conditional variance estimation in regression models with long memory ⋮ Nonparametric estimation in a regression model with additive and multiplicative noise ⋮ Insensitivity of Nadaraya–Watson estimators to design correlation ⋮ Estimation in nonparametric regression model with additive and multiplicative noise via Laguerre series ⋮ Variance function estimation in regression model via aggregation procedures ⋮ Universal kernel-type estimation of random fields ⋮ Long-range dependent time series specification ⋮ Universal weighted kernel-type estimators for some class of regression models ⋮ Local linear estimation for regression models with locally stationary long memory errors ⋮ Kernel density estimation from complex surveys in the presence of complete auxiliary information
Uses Software
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