On the detection of changes in autoregressive time series, II. Resampling procedures

By Marie Husková, Claudia Kirch, Zuzana Prásková, Josef G. Steinebach. 2008

83 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/60ca6837aedba01f970637a1a01d2bab155650e5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Lajos Horv'ath
2. Alexander Aue
3. Siegfried Hormann
4. Claudia Kirch
5. Marie Husková
6. Josef G. Steinebach
7. Idris Arthur Eckley
8. Paul Fearnhead

In Statistics and Probability

1. Lajos Horv'ath
2. Alexander Aue
3. Claudia Kirch
4. Marie Husková
5. Siegfried Hormann
6. Gregory Rice
7. Josef G. Steinebach
8. Paul Fearnhead

Citations in the corpus

• Structural breaks in time series (2013, methodology): “…gnðkÞg: Sequential tests based on CUSUM-based detector functions were considered in Aue et al. (2006, 2009) and Horváth et al. (2004) for linear and time series regressions, in Gombay and Serban (2009), Hušková et al. (2007) for AR processes, and in Berkes et al. (2004) for GARCH processes.”
• SEQUENTIAL TESTING FOR THE STABILITY OF HIGH-FREQUENCY PORTFOLIO BETAS (2011, methodology): “Modifications have since been applied successfully in various settings, including autoregressive processes (Hušková, Prǎsková, and Steinebach, 2007), generalized autoregressive conditional heteroskedastic processes (Berkes, Gombay, Horváth, and Kokoszka, 2004), and multiple time series…”
• DEPENDENT FUNCTIONAL LINEAR MODELS WITH APPLICATIONS TO MONITORING STRUCTURAL CHANGE (2014, unknown): “Contributions to the area include, but are not limited to, Leisch, Hornik, and Kuan (2000), Zeileis et al. (2005), Aue et al.”
• Delay times of sequential procedures for multiple time series regression models (2009, unknown): “Berkes et al. (2004) discussed the problem of sequentially detecting change-points in the parameters of GARCH(p, q) processes, while Hušková et al. (2007) analyzed the stability of autoregressive time series.”
• Changepoints in times series of counts (2012, methodology): “Davis et al. (1995) obtain a Gaussian-type likelihood ratio statistic which is related to the approach using weighted sums of residuals by Huŝkova et al. (2007), both of which have power against a larger class of residuals than statistics based on partial sums of residuals.”
• Optimal detection of changepoints with a linear computational cost (2011, methodology): “For the data we consider (Figure 4 (2006), Huskova et al. (2007) and Gombay (2008).”