Statistics
Exchangeably weighted bootstraps of empirical estimators of a semi-Markov kernel
[Le bootstrap échangeable pondéré de lʼestimateur empirique du noyau semi-markovien]
Comptes Rendus. Mathématique, Tome 351 (2013) no. 13-14, pp. 569-573.

Nous introduisons la notion du bootstrap échangeable des estimateurs empiriques des noyaux semi-markoviens et des probabilités de transition conditionnelles pour les processus semi-markoviens à espace dʼétat dénombrable. Nous obtenons nos résultats asymptotiques en utilisant les approches martingales.

A general notion of bootstrapped empirical estimators, of the semi-Markov kernels and of the conditional transition probabilities for semi-Markov processes with countable state space, constructed by exchangeably weighting sample, is introduced. Asymptotic properties of these generalized bootstrapped empirical distributions are obtained by means of the martingale approach.

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Accepté le :
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DOI : 10.1016/j.crma.2013.07.013
Bouzebda, Salim 1 ; Limnios, Nikolaos 1

1 Laboratoire de mathématiques appliquées de Compiègne, université de technologie de Compiègne, CS 60319, 60205 Compiègne cedex, France
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Bouzebda, Salim; Limnios, Nikolaos. Exchangeably weighted bootstraps of empirical estimators of a semi-Markov kernel. Comptes Rendus. Mathématique, Tome 351 (2013) no. 13-14, pp. 569-573. doi : 10.1016/j.crma.2013.07.013. http://www.numdam.org/articles/10.1016/j.crma.2013.07.013/

[1] Andersen, P.K.; Borgan, Ø.; Gill, R.D.; Keiding, N. Statistical Models Based on Counting Processes, Springer Series in Statistics, Springer-Verlag, New York, 1993

[2] Barbe, P.; Bertail, P. The Weighted Bootstrap, Lecture Notes in Statistics, vol. 98, Springer-Verlag, New York, 1995

[3] Barbu, V.S.; Limnios, N. Semi-Markov Chains and Hidden Semi-Markov Models toward Applications: Their Use in Reliability and DNA Analysis, Lecture Notes in Statistics, vol. 191, Springer, New York, 2008

[4] Beran, R. The impact of the bootstrap on statistical algorithms and theory, Stat. Sci., Volume 18 (2003) no. 2, pp. 175-184

[5] Berkes, I.; Philipp, W. Approximation theorems for independent and weakly dependent random vectors, Ann. Probab., Volume 7 (1979) no. 1, pp. 29-54

[6] Bickel, P.J.; Freedman, D.A. Some asymptotic theory for the bootstrap, Ann. Stat., Volume 9 (1981) no. 6, pp. 1196-1217

[7] Bickel, P.J.; Götze, F.; van Zwet, W.R. Resampling fewer than n observations: gains, losses, and remedies for losses, New Brunswick, NJ, 1995 (Stat. Sin.), Volume 7 (1997) no. 1, pp. 1-31

[8] S. Bouzebda, N. Limnios, On a multidimensional general bootstrap for empirical estimator of continuous-time semi-Markov kernels with applications, 2013, submitted for publication.

[9] Bouzebda, S.; Limnios, N. On general bootstrap of empirical estimator of a semi-Markov kernel with applications, J. Multivar. Anal., Volume 116 (2013), pp. 52-62

[10] Cheng, G.; Huang, J.Z. Bootstrap consistency for general semiparametric M-estimation, Ann. Stat., Volume 38 (2010) no. 5, pp. 2884-2915

[11] Csörgő, M.; Horváth, L. Weighted Approximations in Probability and Statistics, Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics, John Wiley & Sons Ltd., Chichester, 1993

[12] Csörgő, M.; Révész, P. Strong Approximations in Probability and Statistics, Probability and Mathematical Statistics, Academic Press Inc. [Harcourt Brace Jovanovich Publishers], New York, 1981

[13] Efron, B. Bootstrap methods: another look at the jackknife, Ann. Stat., Volume 7 (1979) no. 1, pp. 1-26

[14] Semi-Markov Models and Applications (Janssen, J.; Limnios, N., eds.), Kluwer Academic Publishers, Dordrecht, 1999 (Selected papers from the 2nd International Symposium on Semi-Markov Models: Theory and Applications held in Compiègne, December 1998)

[15] Kosorok, M.R. Introduction to Empirical Processes and Semiparametric Inference, Springer Series in Statistics, Springer, New York, 2008

[16] Limnios, N. A functional central limit theorem for the empirical estimator of a semi-Markov kernel, J. Nonparametr. Stat., Volume 16 (2004) no. 1–2, pp. 13-18

[17] Limnios, N.; Oprişan, G. Semi-Markov Processes and Reliability, Statistics for Industry and Technology, Birkhäuser Boston Inc., Boston, MA, 2001

[18] Mason, D.M.; Newton, M.A. A rank statistics approach to the consistency of a general bootstrap, Ann. Stat., Volume 20 (1992) no. 3, pp. 1611-1624

[19] Præstgaard, J.; Wellner, J.A. Exchangeably weighted bootstraps of the general empirical process, Ann. Probab., Volume 21 (1993) no. 4, pp. 2053-2086

[20] Pyke, R. Markov renewal processes: definitions and preliminary properties, Ann. Math. Stat., Volume 32 (1961), pp. 1231-1242

[21] Pyke, R. Markov renewal processes with finitely many states, Ann. Math. Stat., Volume 32 (1961), pp. 1243-1259

[22] Rubin, D.B. The Bayesian bootstrap, Ann. Stat., Volume 9 (1981) no. 1, pp. 130-134

[23] van der Vaart, A.W.; Wellner, J.A. Weak Convergence and Empirical Processes: With Applications to Statistics, Springer Series in Statistics, Springer-Verlag, New York, 1996

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