Periodically correlated time series and the Variable Bandpass Periodic Block Bootstrap.

ABSTRACT: This research introduces a novel approach to resampling periodically correlated time series using bandpass filters for frequency separation called the Variable Bandpass Periodic Block Bootstrap and then examines the significant advantages of this new method. While bootstrapping allows estimation of a statistic's sampling distribution by resampling the original data with replacement, and block bootstrapping is a model-free resampling strategy for correlated time series data, both fail to preserve correlations in periodically correlated time series. Existing extensions of the block bootstrap help preserve the correlation structures of periodically correlated processes but suffer from flaws and inefficiencies. Analyses of time series data containing cyclic, seasonal, or periodically correlate

SUBMITTER: Valachovic EL 

PROVIDER: S-EPMC11407666 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature