Abstract
In this paper we consider the problem of testing for a parameter change based on the cusum test proposed by Leeet al. (2003,Scandinavian Journal of Statistics,30, 781–796). The cusum test statistic is constructed via employing the estimator minimizing density-based divergence measures. It is shown that under regularity conditions, the test statistic has the limiting distribution of the sup of standard Brownian bridge. Simulation results demonstrate that the cusum test is robust when outliers exist.
Similar content being viewed by others
References
Basu, A. and Lindsay, B. G. (1994). Minimum disparity estimation for continous models: Efficiency, distributions and robustness,Annals of the Institute of Statistical Mathematics,46, 683–705.
Basu, A., Harris, I. R., Hjort, N. L. and Jones, M. C. (1998). Robust and efficient estimation by minimizing a density power divergence,Biometrika,85, 549–559.
Beran, R. (1977). Minimum hellinger distance estimates for parametric models,Annals of Statistics,5, 445–463.
Bosq, D. (1996).Nonparametric Statistics for Stochastic Processes; Estimation and Prediction, Lecture Notes in Statistics, No. 10, Springer, New York.
Bustos, O. H. (1982). GeneralM-estimates for contaminatedpth-order autoregressive processes: Consistency and asymptotic normality,Zeitschrift fur Wahrscheinlichkeitstheorie und verwandte Gebiete,59, 491–504.
Cao, R., Cuevas, A. and Fraiman, R. (1995). Minimum distance density-based estimation,Computational Statistics and Data Analysis,20, 611–631.
Chan, J. and Gupta, A. K. (2000),Parametric Statistical Change Point Analysis, Birkhäuser, Boston.
Csörgö, M. and Horváth, L. (1997),Limit Theorems in Change-point Analysis, Wiley, New York.
Denby, L. and Martin, D. (1979). Robust estimation of the first-order autoregressive parameter,Journal of the American Statistical Association,74, 140–146.
Ferguson, T. S. (1996).A Course in Large Sample Theory, Chapman & Hall, London.
Fox, A. J. (1972). Outliers in time series,Journal of the Royal Statistical Society. Series B,34, 350–363.
Hong, C. and Kim, Y. (2001). Automatic selection of the tuning parameter in the minimum density power divergence estimation,Journal of the Korean Statistical Society,30, 453–465.
Inclán, C. and Tiao, G. C. (1994). Use of cumulative sums of squares for retrospective detection of changes of variances,Journal of the American Statistical Association,89, 913–923.
Lee, S. and Park, S. (2001). The cusum of squares test for scale changes in infinite order moving average processes,Scandinavian Journal of Statistics,28, 625–644.
Lee, S., Ha, J., Na, O. and Na, S. (2003). The cusum test for parameter change in time series models,Scandinavian Journal of Statistics,30, 781–796.
Page, E. S. (1955). A test for change in a parameter occurring at an unknown point.Biometrika,42, 523–527.
Peligrad, M. (1986). Recent advances in the central limit theorem and its weak invariance principle for mixing sequences of random variables (a survey),Dependence in Probability and Statistics eds. (E. Eberlein and M. S. Taqqu), 193–223, Birkhäuser, Boston.
Simpson, D. G. (1987). Minimum hellinger distance estimation for the analysis of count data.Journal of the American Statistical Association,82, 802–807.
Tamura, R. N. and Boos, D. D. (1986). Minimum hellinger distance estimation for multivariate location and covariance,Journal of the American Statistical Association,81, 223–239.
Author information
Authors and Affiliations
About this article
Cite this article
Lee, S., Na, O. Test for parameter change based on the estimator minimizing density-based divergence measures. Ann Inst Stat Math 57, 553–573 (2005). https://doi.org/10.1007/BF02509239
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02509239