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Computational Statistics

, Volume 17, Issue 4, pp 517–524 | Cite as

On Single Versus Multiple Imputation for a Class of Stochastic Algorithms Estimating Maximum Likelihood

  • Edward H. Ip
Article

Summary

We discuss a special class of stochastic versions of the EM algorithms. The advantage of the single imputation procedure in non-exponential family applications is highlighted. We prove that ergodic properties of the stochastic algorithms are dependent not on the multiplicity of the imputation scheme but rather on the stability of the deterministic component of an underlying stochastic difference equation.

Keywords

EM algorithm non-exponential family Markov chain stochastic difference equation 

Notes

Acknowledgement

This paper is a modified version of a chapter from the author’s doctoral dissertation. The author thanks both Jean Diebolt and Ingram Olkin for their guidance, and for suggestions to this paper.

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Copyright information

© Physica-Verlag 2002

Authors and Affiliations

  • Edward H. Ip
    • 1
  1. 1.Marshall School of BusinessUniversity of Southern CaliforniaLos AngelesUSA

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