Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence

DOI10.2307/3315382zbMath0858.62029OpenAlexW2084826183MaRDI QIDQ4891289

Graciela Boente, Ricardo Fraiman

Publication date: 3 September 1996

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315382

zbMATH Keywords

kernel estimatesdensity estimationnonparametric regressiondependent observationsalpha-mixing processesfirst-order asymptotic approximationdata-driven bandwidth selectorsrandom bandwidth selector

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

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Estimation of conditional \(L_1\)-median from dependent observations, Mean squared error properties of the kernel-based multi-stage median predictor for time series, On Asymptotic Normality of the Local Polynomial Regression Estimator with Stochastic Bandwidths, Adaptive estimation in partially linear autoregressive models, Bandwidth choice for robust nonparametric scale function estimation, Robust nonparametric estimation with missing data, A Multivariate Quantile Predictor, A Simple Data-Driven Estimator for the Semiparametric Sample Selection Model

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