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All issues Volume 12 (April 2008) ESAIM: PS, 12 (2008) 308-326 References
Free Access
Issue
ESAIM: PS
Volume 12, April 2008
Page(s) 308 - 326
DOI https://doi.org/10.1051/ps:2007041
Published online 08 May 2008
  1. H. Ahn, H. Moon and R.L. Kodell, Attribution of tumour lethality and estimation of the time to onset of occult tumours in the absence of cause-of-death information. J. Roy. Statist. Soc. Ser. C 49 (2000) 157–169. [CrossRef] [MathSciNet] [Google Scholar]
  2. M.J. Box, A new method of constrained optimization and a comparison with other methods. Comp. J. 8 (1965) 42–52. [Google Scholar]
  3. G. Celeux, S. Chretien, F. Forbes and A. Mkhadri, A component-wise EM algorithm for mixtures. J. Comput. Graph. Statist. 10 (2001), 697–712 and INRIA RR-3746, Aug. 1999. [Google Scholar]
  4. S. Chretien and A.O. Hero, Acceleration of the EM algorithm via proximal point iterations, in Proceedings of the International Symposium on Information Theory, MIT, Cambridge (1998) 444. [Google Scholar]
  5. S. Chrétien and A. Hero, Kullback proximal algorithms for maximum-likelihood estimation. IEEE Trans. Inform. Theory 46 (2000) 1800–1810. [CrossRef] [MathSciNet] [Google Scholar]
  6. I. Csiszár, Information-type measures of divergence of probability distributions and indirect observations. Studia Sci. Math. Hung. 2 (1967) 299–318. [Google Scholar]
  7. A.P. Dempster, N.M. Laird and D.B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Statist. Soc., Ser. B 39 (1977) 1–38. [Google Scholar]
  8. I.A. Ibragimov and R.Z. Has'minskii, Statistical estimation: Asymptotic theory. Springer-Verlag, New York (1981). [Google Scholar]
  9. Journal of Statistical Planning and Inference No. 107 (2002) 1–2. [Google Scholar]
  10. A.T. Kalai and S. Vempala, Simulated annealing for convex optimization. Math. Oper. Res. 31 (2006) 253–266. [CrossRef] [MathSciNet] [Google Scholar]
  11. B. Martinet, Régularisation d'inéquation variationnelles par approximations successives. Revue Francaise d'Informatique et de Recherche Operationnelle 3 (1970) 154–179. [Google Scholar]
  12. G.J. McLachlan and T. Krishnan, The EM algorithm and extensions, Wiley Series in Probability and Statistics: Applied Probability and Statistics. John Wiley and Sons, Inc., New York (1997). [Google Scholar]
  13. H. Moon, H. Ahn, R. Kodell and B. Pearce, A comparison of a mixture likelihood method and the EM algorithm for an estimation problme in animal carcinogenicity studies. Comput. Statist. Data Anal. 31 (1999) 227–238. [CrossRef] [Google Scholar]
  14. A.M. Ostrowski, Solution of equations and systems of equations. Pure and Applied Mathematics, Vol. IX. Academic Press, New York-London (1966). [Google Scholar]
  15. R.T. Rockafellar, Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14 (1976) 877–898. [CrossRef] [Google Scholar]
  16. M. Teboulle, Entropic proximal mappings with application to nonlinear programming. Math. Oper. Res. 17 (1992) 670–690. [CrossRef] [MathSciNet] [Google Scholar]
  17. P. Tseng, An analysis of the EM algorithm and entropy-like proximal point methods. Math. Oper. Res. 29 (2004) 27–44. [CrossRef] [MathSciNet] [Google Scholar]
  18. C.F.J. Wu, On the convergence properties of the EM algorithm. Ann. Stat. 11 (1983) 95–103. [Google Scholar]
  19. Z.B. Zabinsky, Stochastic adaptive search for global optimization. Nonconvex Optimization and its Applications 72. Kluwer Academic Publishers, Boston, MA (2003). [Google Scholar]
  20. W.I. Zangwill and B. Mond, Nonlinear programming: a unified approach. Prentice-Hall International Series in Management. Prentice-Hall, Inc., Englewood Cliffs, N.J. (1969). [Google Scholar]

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