Changepoint Detection in Periodic and Autocorrelated Time Series

By Robert B. Lund, Xiaolan L. Wang, Q. Lu, Jaxk Reeves, Colin M. Gallagher, Yang Feng. 2007

130 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/05b57148d63229e457ba6e76a599da85c07bdf21

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

1. Xiaolan L. Wang
2. Yuehua Wu
3. M. Menne
4. C. Naomie Williams
5. Peter Guttorp
6. Marc G. Genton
7. Konstantinos Fokianos
8. P. Domonkos

In Global and Planetary Change

1. Xiaolan L. Wang
2. M. Menne
3. C. Naomie Williams
4. Yuehua Wu
5. Peter Guttorp
6. Qiuzi Han Wen
7. Peter F. Craigmile
8. P. Domonkos

In Statistics and Probability

1. Xiaolan L. Wang
2. M. Menne
3. C. Naomie Williams
4. Yuehua Wu
5. Qiuzi Han Wen
6. Q. Lu
7. Jien Chen
8. Robert B. Lund

Citations in the corpus

• Homogenization of Temperature Series via Pairwise Comparisons (2009, background): “Following Lund et al. (2007), these two series can be represented as XmT1n 5 m X v 1 b X(mT 1 n) 1 dXmT1n 1 « X mT1n (1) and YmT1n 5 m Y v 1 b Y(mT 1 n) 1 dYmT1n 1 « Y mT1n, (2) where m represents the monthly mean anomaly at the specific series, T 5 12 represents the months in the annual cycle, n 2…”
• Penalized Maximal F Test for Detecting Undocumented Mean Shift without Trend Change (2008, methodology): “Recently, Lund et al. (2007) addressed this need, proposing a new method for changepoint detection in periodic and autocorrelated time series.”
• Accounting for Autocorrelation in Detecting Mean Shifts in Climate Data Series Using the Penalized Maximal t or F Test (2008, methodology): “Note that the computation-demanding method of Lund et al. (2007) is also an empirical approach in the sense that the theoretical distribution of the test statistic is unknown; in addition, it has a drawback that the percentiles of its test statistic depend on the time series parameters and hence…”
• Space‐time modelling of trends in temperature series (2011, background): “Analyses of temperature data in space and time play a crucial role in studying climate change.”
• Penalized Maximal t Test for Detecting Undocumented Mean Change in Climate Data Series (2007, methodology): “Lund et al. (2007) recently proposed a new method for changepoint detection in periodic and autocorrelated time series, although the effect of unequal sample sizes is yet to be taken into account in this new method.”
• A Review and Comparison of Changepoint Detection Techniques for Climate Data (2007, background): “An article that does exactly this is Lund et al. (2007). One conclusion therein is that changepoint detection procedures developed for independent error series when positive autocorrelation is truly present will result in the detection of too many false changepoints.”