The Impact of Bootstrap Methods on Time Series Analysis

By Dimitris Nicolas Politis. 2003

353 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/962e99d4e7d7bfcddb8be31527b6d8a6e8c8c54e

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Citations in the corpus

Habitat use, movements and site fidelity of the gray smooth-hound shark (Mustelus californicus Gill 1863) in a newly restored southern California estuary (2011, methodology): “Additionally, sample locations were randomly selected from each shark using a bootstrapping approach in order to correct for autocorrelation in time-series data (Politis, 2003; Rogers and White, 2007).”
Density Forecasting for Long-Term Peak Electricity Demand (2010, methodology): “for bootstrapping time series is the “block bootstrap” [24] which”
Resampling Methods for Dependent Data (2005, background): “One article in particular (Politis 2003) provides a very compact current review of the area.”
Bootstrap Methods in Econometrics (2006, neutral): “These include B¨uhlmann (2002), Politis (2003) , and H¨ardle, Horowitz, and Kreiss (2003).”
On the range of validity of the autoregressive sieve bootstrap (2012, background): “For an overview see Bühlmann (2002), Lahiri (2003), Politis (2003) and Paparoditis and Politis (2009).”
TFT-bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain (2011, background): “Bühlmann [6], Lahiri [36] and Politis [50] give reviews of the state-of-the-art in resampling time series and dependent data.”
A Comprehensive set of Postestimation Measures to Enrich Interrupted Time-series Analysis (2017, methodology): “Further, understanding how to derive measures that capture the components of ITSA may serve as a helpful framework for understanding similar components of more complex models, such as arima, and for exploring alternative estimation using bootstrapping techniques (Politis 2003).”