Joint segmentation of multivariate Gaussian processes using mixed linear models
AbstractThe joint segmentation of multiple series is considered. A mixed linear model is used to account for both covariates and correlations between signals. An estimation algorithm based on EM which involves a new dynamic programming strategy for the segmentation step is proposed. The computational efficiency of this procedure is shown and its performance is assessed through simulation experiments. Applications are presented in the field of climatic data analysis.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 55 (2011)
Issue (Month): 2 (February)
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Segmentation Mixed linear model Multivariate Gaussian process Dynamic programming EM algorithm;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Henri Caussinus & Olivier Mestre, 2004. "Detection and correction of artificial shifts in climate series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 405-425.
- Jushan Bai & Pierre Perron, 2003.
"Computation and analysis of multiple structural change models,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
- Tom Doan, . "BAIPERRON: RATS procedure to perform Bai-Perron Test for Multiple Structural Changes," Statistical Software Components RTS00013, Boston College Department of Economics.
- Tom Doan, . "RATS programs to replicate examples of Bai-Perron procedure," Statistical Software Components RTZ00008, Boston College Department of Economics.
- BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
- Tom Doan, . "MULTIPLEBREAKS: RATS procedure to perform multiple structural change analysis," Statistical Software Components RTS00138, Boston College Department of Economics.
- Dobigeon, Nicolas & Tourneret, Jean-Yves, 2007. "Joint segmentation of wind speed and direction using a hierarchical model," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5603-5621, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.