Inference for mean change-point in infinite variance \(AR(p)\) process

DOI10.1016/j.spl.2008.05.040zbMath1152.62375OpenAlexW1985084706MaRDI QIDQ2518944

Jie Zhou, San-Yang Liu

Publication date: 21 January 2009

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2008.05.040

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03) Asymptotic properties of parametric tests (62F05)

Related Items (4)

The CUSUM Test for Detecting Structural Changes in Strong Mixing Processes ⋮ A quasi-Bayesian change point detection with exchangeable weights ⋮ Randomised pseudolikelihood ratio change point estimator in GARCH models ⋮ Strong convergence rate of robust estimator of change point

Cites Work

• Unnamed Item
• Unnamed Item
• The effect of long-range dependence on change-point estimators
• Some mixing properties of time series models
• Approximating the distribution of the maximum likelihood estimate of the change-point in a sequence of independent random variables
• Mixing: Properties and examples
• \(L_{p}\)-estimators in ARCH models
• Change-point estimation in ARCH models
• LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES
• Truncating Estimation for the Mean Change-Point in Heavy-Tailed Dependent Observations
• Self-Weighted Least Absolute Deviation Estimation for Infinite Variance Autoregressive Models
• Inference about the change-point in a sequence of random variables

This page was built for publication: Inference for mean change-point in infinite variance \(AR(p)\) process