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]
  2. M.J. Box, A new method of constrained optimization and a comparison with other methods. Comp. J. 8 (1965) 42–52.
  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.
  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.
  5. S. Chrétien and A. Hero, Kullback proximal algorithms for maximum-likelihood estimation. IEEE Trans. Inform. Theory 46 (2000) 1800–1810. [CrossRef] [MathSciNet]
  6. I. Csiszár, Information-type measures of divergence of probability distributions and indirect observations. Studia Sci. Math. Hung. 2 (1967) 299–318.
  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.
  8. I.A. Ibragimov and R.Z. Has'minskii, Statistical estimation: Asymptotic theory. Springer-Verlag, New York (1981).
  9. Journal of Statistical Planning and Inference No. 107 (2002) 1–2.
  10. A.T. Kalai and S. Vempala, Simulated annealing for convex optimization. Math. Oper. Res. 31 (2006) 253–266. [CrossRef] [MathSciNet]
  11. B. Martinet, Régularisation d'inéquation variationnelles par approximations successives. Revue Francaise d'Informatique et de Recherche Operationnelle 3 (1970) 154–179.
  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).
  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]
  14. A.M. Ostrowski, Solution of equations and systems of equations. Pure and Applied Mathematics, Vol. IX. Academic Press, New York-London (1966).
  15. R.T. Rockafellar, Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14 (1976) 877–898. [CrossRef]
  16. M. Teboulle, Entropic proximal mappings with application to nonlinear programming. Math. Oper. Res. 17 (1992) 670–690. [CrossRef] [MathSciNet]
  17. P. Tseng, An analysis of the EM algorithm and entropy-like proximal point methods. Math. Oper. Res. 29 (2004) 27–44. [CrossRef] [MathSciNet]
  18. C.F.J. Wu, On the convergence properties of the EM algorithm. Ann. Stat. 11 (1983) 95–103. [CrossRef] [MathSciNet]
  19. Z.B. Zabinsky, Stochastic adaptive search for global optimization. Nonconvex Optimization and its Applications 72. Kluwer Academic Publishers, Boston, MA (2003).
  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).

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