This article is published in Environmetrics as a special issue on TIES 2008: Quantitative Methods for Environmental Sustainability, edited by Sylvia R. Esterby, University of British Columbia Okanagan, Canada.
Special Issue Paper
Change-point analysis of mean annual rainfall data from Tucumán, Argentina†
Version of Record online: 12 FEB 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Special Issue: TIES 2008: Quantitative methods for environmental sustainability
Volume 21, Issue 7-8, pages 687–697, November - December 2010
How to Cite
Jandhyala, V. K., Fotopoulos, S. B. and You, J. (2010), Change-point analysis of mean annual rainfall data from Tucumán, Argentina. Environmetrics, 21: 687–697. doi: 10.1002/env.1038
- Issue online: 12 FEB 2010
- Version of Record online: 12 FEB 2010
- Manuscript Accepted: 9 NOV 2009
- Manuscript Received: 4 NOV 2008
- National Science Foundation. Grant Number: DMS-0806133
- annual rainfall;
- Bayes-type test;
- likelihood ratio test;
- maximum likelihood estimate;
- moving average
The annual mean rainfall data from Tucumán, Argentina for the years 1884–1996 is revisited for an in-depth change-point analysis. Applying classical change detection statistics, we first demonstrate that change-point analysis under independence is invalid. Upon properly adjusting for dependence, it is found that a significant change has occurred in the mean of the data in and around 1956. The data analysis demonstrates that change detection statistics are sensitive to how the model variance is estimated. Moreover, the analysis shows that even marginally significant serial correlations among the observations can have a highly significant effect upon the variance estimate. Finally, the analysis illustrates that one should exercise care while implementing parametric or non-parametric methods in estimating the model variance, and one should be prepared for one of the methods outperforming the other. Copyright © 2010 John Wiley & Sons, Ltd.