Bootstrapping the empirical distribution of a stationary process with change-point

DOI10.1214/19-EJS1613zbMath1431.62180MaRDI QIDQ2326067

Farid El Ktaibi, B. Gail Ivanoff

Publication date: 4 October 2019

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1569895283

zbMATH Keywords

time serieschange-pointsequential empirical processcausal linear processmoving block bootstrap

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Order statistics; empirical distribution functions (62G30) Stationary stochastic processes (60G10) Nonparametric statistical resampling methods (62G09) Functional limit theorems; invariance principles (60F17)

Related Items (3)

Incorporating a change-point estimator when bootstrapping the empirical distribution of a stationary process ⋮ Weak convergence for stationary bootstrap empirical processes of associated sequences ⋮ Asymptotic properties of \(M\)-estimators based on estimating equations and censored data in semi-parametric models with multiple change points

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