Free Access
Volume 15, 2011
Page(s) 1 - 29
Published online 22 February 2011
  1. M. Aerts and N. Veraverbeke, Bootstrapping a nonparametric polytomous regression model. Math. Meth. Statist. 4 (1995) 189–200. [Google Scholar]
  2. Y. Baraud and L. Birgé, Estimating the intensity of a random measure by histogram type estimators. Prob. Theory Relat. Fields 143 (2009) 239–284. [Google Scholar]
  3. A. Barron, L. Birgé and P. Massart, Risk bounds for model selection via penalization. Prob. Theory Relat. Fields 113 (1999) 301–413. [Google Scholar]
  4. C. Bennett and R. Sharpley, Interpolation of operators, volume 129 of Pure and Applied Mathematics. Academic Press Inc., Boston, M.A. (1988). [Google Scholar]
  5. L. Birgé, Model selection via testing: an alternative to (penalized) maximum likelihood estimators. Ann. Inst. H. Poincaré Probab. Statist. 42 (2006) 273–325. [Google Scholar]
  6. L. Birgé, Model selection for Poisson processes, in Asymptotics: Particles, Processes and Inverse Problems, Festschrift for Piet Groeneboom. IMS Lect. Notes Monograph Ser. 55. IMS, Beachwood, USA (2007) 32–64. [Google Scholar]
  7. L. Birgé and P. Massart, Minimal penalties for Gaussian model selection. Prob. Theory Relat. Fields 138 (2007) 33–73. [Google Scholar]
  8. J.V. Braun and H.-G. Müller, Statistical methods for DNA sequence segmentation. Stat. Sci. 13 (1998) 142–162. [CrossRef] [Google Scholar]
  9. J.V. Braun, R.K. Braun and H.-G. Müller, Multiple changepoint fitting via quasilikelihood, with application to DNA sequence segmentation. Biometrika 87 (2000) 301–314. [CrossRef] [MathSciNet] [Google Scholar]
  10. T.H. Cormen, C.E. Leiserson, R.L. Rivest and C. Stein, Introduction to algorithms. Second edition. MIT Press, Cambridge, MA (2001). [Google Scholar]
  11. M. Csűrös, Algorithms for finding maximum-scoring segment sets, in Proc. of the 4th international workshop on algorithms in bioinformatics 2004. Lect. Notes Comput. Sci. 3240. Springer, Berlin, Heidelberg (2004) 62–73. [Google Scholar]
  12. R.A. DeVore and G.G. Lorentz, Constructive approximation. Springer-Verlag, Berlin, Heidelberg (1993). [Google Scholar]
  13. R.A. DeVore and R.C. Sharpley, Maximal functions measuring smoothness. Mem. Amer. Math. Soc. 47 (1984) 293. [Google Scholar]
  14. R.A. DeVore and X.M. Yu, Degree of adaptive approximation. Math. Comp. 55 (1990) 625–635. [CrossRef] [MathSciNet] [Google Scholar]
  15. C. Durot, E. Lebarbier and A.-S. Tocquet, Estimating the joint distribution of independent categorical variables via model selection. Bernoulli 15 (2009) 475–507. [CrossRef] [MathSciNet] [Google Scholar]
  16. Y.-X. Fu and R.N. Curnow, Maximum likelihood estimation of multiple change points. Biometrika 77 (1990) 562–565. [Google Scholar]
  17. S. Gey S. and E. Lebarbier, Using CART to detect multiple change-points in the mean for large samples. SSB preprint, Research report No. 12 (2008). [Google Scholar]
  18. M. Hoebeke, P. Nicolas and P. Bessières, MuGeN: simultaneous exploration of multiple genomes and computer analysis results. Bioinformatics 19 (2003) 859–864. [CrossRef] [PubMed] [Google Scholar]
  19. E. Lebarbier, Quelques approches pour la détection de ruptures à horizon fini. Ph.D. thesis, Université Paris Sud, Orsay, 2002. [Google Scholar]
  20. E. Lebarbier and E. Nédélec, Change-points detection for discrete sequences via model selection. SSB preprint, Research Report No. 9 (2007). [Google Scholar]
  21. P. Massart, Concentration inequalities and model selection. Lectures from the 33rd Summer School on Probability Theory held in Saint-Flour, July 6–23, 2003. Lect. Notes Math. 1896. Springer, Berlin, Heidelberg (2007). [Google Scholar]
  22. P. Nicolas et al., Mining Bacillus subtilis chromosome heterogeneities using hidden Markov models. Nucleic Acids Res. 30 (2002) 1418–1426. [CrossRef] [PubMed] [Google Scholar]
  23. W. Szpankowski, L. Szpankowski and W. Ren, An optimal DNA segmentation based on the MDL principle. Int. J. Bioinformatics Res. Appl. 1 (2005) 3–17. [CrossRef] [Google Scholar]

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