Testing for changes in polynomial regression
By Alexander Aue, Lajos Horv'ath, M. Huvskov'a, Piotr Kokoszka. 2008
47 citations recorded by the source corpus.
We consider a nonlinear polynomial regression model in which we wish to test the null hypothesis of structural stability in the regression parameters against the alternative of a break at an unknown time. We derive the extreme value distribution of a maximum-type test statistic which is asymptotically equivalent to the maximally selected likelihood ratio. The resulting test is easy to apply and has good size and power, even in small samples.
Subfields: Economics and Econometrics, Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a85579e14a9c2290e15d416796782d0e49951c89
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Xianyang Zhang
- Gregory Rice
- Zhou Zhou
- Lajos Horv'ath
- Xiaofeng Shao
- Alexander Aue
- Moritz Jirak
- Wei Biao Wu
In Finance
- Xianyang Zhang
- Gregory Rice
- Zhou Zhou
- Lajos Horv'ath
- Xiaofeng Shao
- Alexander Aue
- Holger Dette
- Moritz Jirak
In Statistics and Probability
- Xianyang Zhang
- Zhou Zhou
- Gregory Rice
- Xiaofeng Shao
- Lajos Horv'ath
- Moritz Jirak
- Holger Dette
- Piotr Kokoszka
Citations in the corpus
- Heteroscedasticity and Autocorrelation Robust Structural Change Detection (2013, background): “…Gombay, and Horváth (2009) and Galeano and Pena (2007) for change detection in the autocovariance function, and Brown, Durbin, and Evans (1975), Davis, Huang, and Yao (1995), Kokoszka and Leipus (2000), and Aue et al. (2008) for structural stability tests for various time series regression models.”
- Testing for Change Points in Time Series (2010, methodology): “KEY WORDS: CUSUM; Invariance principle; Self-normalization.”
- Extensions of some classical methods in change point analysis (2014, methodology): “For details we refer to Aue et al. (2008b).”