Bootstrapping stationary sequences by the Nadaraya-Watson regression estimator

DOI10.1080/10485250213116zbMath1022.62041OpenAlexW1970577762MaRDI QIDQ4796544

Cheolyong Park, Tae Yoon Kim

Publication date: 2 November 2003

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

Full work available at URL: https://doi.org/10.1080/10485250213116

zbMATH Keywords

bootstraptime series dataNadaraya-Watson regression estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nonparametric statistical resampling methods (62G09)

Cites Work

• Bootstrap in Markov-sequences based on estimates of transition density
• On bootstrapping two-stage least-squares estimates in stationary linear models
• Nonparametric regression estimation under mixing conditions
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Edgeworth correction by bootstrap in autoregressions
• Nonparametric function estimation involving time series
• Bootstrap methods: another look at the jackknife
• Matched-block bootstrap for dependent data
• Blockwise bootstrapped empirical process for stationary sequences
• Block length selection in the bootstrap for time series
• Theoretical comparisons of block bootstrap methods
• The jackknife and the bootstrap for general stationary observations
• KERNEL REGRESSION SMOOTHING OF TIME SERIES
• The Stationary Bootstrap
• Data-Based Choice of Batch Size for Simulation Output Analysis
• On blocking rules for the bootstrap with dependent data

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