Detecting abrupt changes in random fields
ESAIM: Probability and Statistics, Tome 6 (2002), pp. 189-209.

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

DOI : 10.1051/ps:2002011
Classification : 60E15, 62C99, 62F12, 62G20, 62M40
Mots clés : detection of change-points, $M$-estimation, penalized $M$-estimation, concentration inequalities, maximal inequalities, mixing
@article{PS_2002__6__189_0,
     author = {Chambaz, Antoine},
     title = {Detecting abrupt changes in random fields},
     journal = {ESAIM: Probability and Statistics},
     pages = {189--209},
     publisher = {EDP-Sciences},
     volume = {6},
     year = {2002},
     doi = {10.1051/ps:2002011},
     mrnumber = {1943147},
     language = {en},
     url = {http://www.numdam.org/articles/10.1051/ps:2002011/}
}
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Chambaz, Antoine. Detecting abrupt changes in random fields. ESAIM: Probability and Statistics, Tome 6 (2002), pp. 189-209. doi : 10.1051/ps:2002011. http://www.numdam.org/articles/10.1051/ps:2002011/

[1] 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. | MR | Zbl

[2] A. Antoniadis, I. Gijbels and B. Macgibbon, 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. | MR | Zbl

[3] Z.D. Bai, C.R. Rao and Y. Wu, Model selection with data-oriented penalty. J. Statist. Plann. Inference 77 (1999) 103-117. | MR | Zbl

[4] A. Barron, L. Birgé and P Massart, Risk bounds for model selection via penalization. Probab. Theory Related Fields 113 (1999) 301-413. | MR | Zbl

[5] M. Basseville and I.V. Nikiforov, Detection of abrupt changes: Theory and application. Prentice Hall Inc. (1993). | MR

[6] B.E. Brodsky and B.S. Darkhovsky, Nonparametric methods in change-point problems. Kluwer Academic Publishers Group (1993). | MR | Zbl

[7] 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. | MR

[8] D. Dacunha-Castelle and E. Gassiat, The estimation of the order of a mixture model. Bernoulli 3 (1997) 279-299. | Zbl

[9] J. Dedecker, Exponential inequalities and functional central limit theorems for random fields. ESAIM P&S 5 (2001) 77. | Numdam | MR | Zbl

[10] P. Doukhan, Mixing. Springer-Verlag, New York (1994). Properties and examples. | MR | Zbl

[11] M. Lavielle, On the use of penalized contrasts for solving inverse problems. Application to the DDC (Detection of Divers Changes) problem (submitted).

[12] M. Lavielle, Detection of multiple changes in a sequence of dependent variables. Stochastic Process. Appl. 83 (1999) 79-102. | MR | Zbl

[13] M. Lavielle and E. Lebarbier, An application of MCMC methods for the multiple change-points problem. Signal Process. 81 (2001) 39-53. | Zbl

[14] M. Lavielle and C. Ludeña, The multiple change-points problem for the spectral distribution. Bernoulli 6 (2000) 845-869. | MR | Zbl

[15] M. Lavielle and E. Moulines, Least-squares estimation of an unknown number of shifts in a time series. J. Time Ser. Anal. 21 (2000) 33-59. | MR | Zbl

[16] 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).

[17] E. Mammen and A.B. Tsybakov, Asymptotical minimax recovery of sets with smooth boundaries. Ann. Statist. 23 (1995) 502-524. | MR | Zbl

[18] P. Massart, Some applications of concentration inequalities to statistics. Ann. Fac. Sci. Toulouse Math. (6) 9 (2000) 245-303. | Numdam | MR | Zbl

[19] F. Móricz, A general moment inequality for the maximum of the rectangular partial sums of multiple series. Acta Math. Hungar. 41 (1983) 337-346. | MR | Zbl

[20] F.A. Móricz, R.J. Serfling and W.F. Stout, Moment and probability bounds with quasisuperadditive structure for the maximum partial sum. Ann. Probab. 10 (1982) 1032-1040. | MR | Zbl

[21] 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. | MR | Zbl

[22] E. Rio, Théorie asymptotique des processus aléatoires faiblement dépendants. Springer (2000). | MR | Zbl

[23] G. Schwarz, Estimating the dimension of a model. Ann. Statist. 6 (1978) 461-464. | MR | Zbl

[24] R.J. Serfling, Contributions to central limit theory for dependent variables. Ann. Math. Statist. 39 (1968) 1158-1175. | MR | Zbl

[25] M. Talagrand, New concentration inequalities in product spaces. Invent. Math. 126 (1996) 505-563. | MR | Zbl

[26] A.W. Van Der Vaart, Asymptotic statistics. Cambridge University Press (1998). | MR | Zbl

[27] A.W. Van Der Vaart and J.A. Wellner, Weak convergence and empirical processes. Springer-Verlag, New York (1996). With applications to statistics. | MR | Zbl

[28] V.N. Vapnik, Statistical learning theory. John Wiley & Sons Inc., New York (1998). | MR | Zbl

[29] Y.-C. Yao, Estimating the number of change-points via Schwarz's criterion. Statist. Probab. Lett. 6 (1988) 181-189. | Zbl

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