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Detecting abrupt changes in random fields

Published online by Cambridge University Press:  15 November 2002

Antoine Chambaz*
Affiliation:
UMR C 8628 du CNRS, Équipe de Probabilités, Statistique et Modélisation, Université Paris-Sud, France; [email protected]. FTR&D, 38 rue du Général Leclerc, 92130 Issy-les-Moulineaux, France.
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Abstract

This paper is devoted to the study of some asymptotic properties of aM-estimator in a framework of detection of abrupt changes inrandom field's distribution. This class of problems includes e.g.recovery of sets. It involves various techniques, including M-estimation method, concentrationinequalities, maximal inequalities for dependent random variables and ϕ-mixing. Penalization of the criterion function when the size of thetrue model is unknown is performed. All the results apply under mild, discussedassumptions. Simple examples are provided.

Type
Research Article
Copyright
© EDP Sciences, SMAI, 2002

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References

H. Akaike, A new look at the statistical model identification. IEEE Trans. Automat. Control AC-19 (1974) 716-723. System identification and time-series analysis.
Antoniadis, A., Gijbels, I. and MacGibbon, B., Non-parametric estimation for the location of a change-point in an otherwise smooth hazard function under random censoring. Scand. J. Statist. 27 (2000) 501-519. CrossRef
Bai, Z.D., Rao, C.R. and Model, Y. Wu selection with data-oriented penalty. J. Statist. Plann. Inference 77 (1999) 103-117. CrossRef
Barron, A., Birgé, L. and Massart, P, Risk bounds for model selection via penalization. Probab. Theory Related Fields 113 (1999) 301-413. CrossRef
M. Basseville and I.V. Nikiforov, Detection of abrupt changes: Theory and application. Prentice Hall Inc. (1993).
B.E. Brodsky and B.S. Darkhovsky, Nonparametric methods in change-point problems. Kluwer Academic Publishers Group (1993).
E. Carlstein, H.-G. Müller and D. Siegmund, Change-point problems. Institute of Mathematical Statistics, Hayward, CA (1994). Papers from the AMS-IMS-SIAM Summer Research Conference held at Mt. Holyoke College, South Hadley, MA July 11-16, 1992.
Dacunha-Castelle, D. and Gassiat, E., The estimation of the order of a mixture model. Bernoulli 3 (1997) 279-299. CrossRef
Dedecker, J., Exponential inequalities and functional central limit theorems for random fields. ESAIM P&S 5 (2001) 77. CrossRef
P. Doukhan, Mixing. Springer-Verlag, New York (1994). Properties and examples.
M. Lavielle, On the use of penalized contrasts for solving inverse problems. Application to the DDC (Detection of Divers Changes) problem (submitted).
Lavielle, M., Detection of multiple changes in a sequence of dependent variables. Stochastic Process. Appl. 83 (1999) 79-102. CrossRef
Lavielle, M. and Lebarbier, E., An application of MCMC methods for the multiple change-points problem. Signal Process. 81 (2001) 39-53. CrossRef
Lavielle, M. and Lude, C. na, The multiple change-points problem for the spectral distribution. Bernoulli 6 (2000) 845-869. CrossRef
Lavielle, M. and Moulines, E., Least-squares estimation of an unknown number of shifts in a time series. J. Time Ser. Anal. 21 (2000) 33-59. CrossRef
G. Lugosi, Lectures on statistical learning theory. Presented at the Garchy Seminar on Mathematical Statistics and Applications, available at http://www.econ.upf.es/~lugosi (2000).
Mammen, E. and Tsybakov, A.B., Asymptotical minimax recovery of sets with smooth boundaries. Ann. Statist. 23 (1995) 502-524. CrossRef
Massart, P., Some applications of concentration inequalities to statistics. Ann. Fac. Sci. Toulouse Math. (6) 9 (2000) 245-303. CrossRef
Móricz, F., A general moment inequality for the maximum of the rectangular partial sums of multiple series. Acta Math. Hungar. 41 (1983) 337-346. CrossRef
Móricz, F.A., Serfling, R.J. and Stout, W.F., Moment and probability bounds with quasisuperadditive structure for the maximum partial sum. Ann. Probab. 10 (1982) 1032-1040. CrossRef
V.V. Petrov, Limit theorems of probability theory. The Clarendon Press Oxford University Press, New York (1995). Sequences of independent random variables, Oxford Science Publications.
E. Rio, Théorie asymptotique des processus aléatoires faiblement dépendants. Springer (2000).
Schwarz, G., Estimating the dimension of a model. Ann. Statist. 6 (1978) 461-464. CrossRef
Serfling, R.J., Contributions to central limit theory for dependent variables. Ann. Math. Statist. 39 (1968) 1158-1175. CrossRef
Talagrand, M., New concentration inequalities in product spaces. Invent. Math. 126 (1996) 505-563. CrossRef
A.W. van der Vaart, Asymptotic statistics. Cambridge University Press (1998).
A.W. van der Vaart and J.A. Wellner, Weak convergence and empirical processes. Springer-Verlag, New York (1996). With applications to statistics.
V.N. Vapnik, Statistical learning theory. John Wiley & Sons Inc., New York (1998).
Yao, Y.-C., Estimating the number of change-points via Schwarz's criterion. Statist. Probab. Lett. 6 (1988) 181-189. CrossRef