A Smooth Block Bootstrap for Statistical Functionals and Time Series. (3rd February 2015)

• Record Type: Journal Article
• Authors: Gregory, Karl B.; Lahiri, Soumendra N.; Nordman, Daniel J.
• Other Names: Cavaliere Giuseppe guestEditor.; Politis Dimitris N. guestEditor.; Rahbek Anders guestEditor.
• Is Part Of: Journal of time series analysis. Volume 36:Number 3(2015:May)
• Page Start: 442
• Page End: 461
• Publication Date: 2015-02-03
• Subjects: L‐estimators -- M‐estimators -- sample quantiles -- tapered block bootstrap -- JEL Primary 62G09 -- Secondary 62G20 -- 62J05 -- 62M10; Time-series analysis -- Periodicals; 519.232
• DOI: 10.1111/jtsa.12117
• Languages: English
• ISSNs: 0143-9782

Abstract

Abstract : Unlike with independent data, smoothed bootstraps have received little consideration for time series, although data smoothing within resampling can improve bootstrap approximations, especially when target distributions depend on smooth population quantities (e.g., marginal densities). For approximating a broad class statistics formulated through statistical functionals (e.g., LL‐estimators, and sample quantiles), we propose a smooth bootstrap by modifying a state‐of‐the‐art (extended) tapered block bootstrap (TBB). Our treatment shows that the smooth TBB applies to time series inference cases not formally established with other TBB versions. Simulations also indicate that smoothing enhances the block bootstrap.