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Parametric Inference for imperfectly observed Gibbsian fields
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  • Published: August 1989

Parametric Inference for imperfectly observed Gibbsian fields

  • Laurent Younes1 

Probability Theory and Related Fields volume 82, pages 625–645 (1989)Cite this article

Summary

This paper presents a maximum likelihood estimation method for imperfectly observed Gibbsian fields on a finite lattice. This method is an adaptation of the algorithm given in Younes [28]. Presentation of the new algorithm is followed by a theorem about the limit of the second derivative of the likelihood when the lattice increases, which is related to convergence of the method. Some practical remarks about the implementation of the procedure are eventually given.

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Authors and Affiliations

  1. Laboratoire de Statistique Appliquée, Université Paris Sud, Bat 425, F-91405, Orsay Cedex, France

    Laurent Younes

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  1. Laurent Younes
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Younes, L. Parametric Inference for imperfectly observed Gibbsian fields. Probab. Th. Rel. Fields 82, 625–645 (1989). https://doi.org/10.1007/BF00341287

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  • Received: 01 April 1988

  • Revised: 15 January 1989

  • Issue Date: August 1989

  • DOI: https://doi.org/10.1007/BF00341287

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Keywords

  • Stochastic Process
  • Estimation Method
  • Probability Theory
  • Maximum Likelihood Estimation
  • Likelihood Estimation
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