BANDWIDTH SELECTION IN KERNEL SMOOTHING OF TIME SERIES

DOI10.1111/j.1467-9892.1996.tb00264.xzbMath0835.62079OpenAlexW2116322238MaRDI QIDQ4870530

Tae Yoon Kim, Dennis D. Cox

Publication date: 20 March 1996

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.1996.tb00264.x

zbMATH Keywords

predictionidentificationkernel smoothingcross-validationasymptotic optimalityautoregressive processsmoothing parametertime series models

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

Recursive regression estimators with application to nonparametric prediction, Neural networks for bandwidth selection in local linear regression of time series, Predictive Inference for Locally Stationary Time Series With an Application to Climate Data, Functional estimation for time series: Uniform convergence properties, sequential estimation of the hgarginal density function for a strongly mixing process, Asymptotic behavior of bandwidth selected by the cross-validation method for local polynomial fitting, The local bootstrap for Markov processes, Nonparametric estimation of structural change points in volatility models for time series

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