Skip to main content
SpringerLink
Log in

Partial Imputation Method in the EM Algorithm

  • Conference paper
Book cover COMPSTAT

Abstract

The expectation maximization(EM) algorithm is a general iterative algorithm for the maximum-likelihood estimation(MLE) in incomplete-data problems. Dempster, Laird and Rubin(1977, henceforth DLR) showed that convergence is linear with rate proportional to the ratio of the missing information to the complete information. When a large proportion of data are missing, the speed of convergence can be very slow.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977), Maximum likelihood estimation from incomplete data via the EM algorithm(with discussion). J. R. Stat. Soc., B39, 1–38.

    MathSciNet  Google Scholar 

  • Geng, Z. (1988), Multidimensional contingency tables with missing data. Communs Statist.-Theory and Meth., 17, 4137–4146.

    Article  MathSciNet  MATH  Google Scholar 

  • Geng, Z., C. Asano, M. Ichimura and H. Kimura (1994), Algorithm AS 294: Decomposability and collapsibility for contingency tables with missing data. App. Statist., 43, 548–554.

    Article  Google Scholar 

  • Meng, X. L. (1994), On the rate of convergence of the ECM algorithm. Ann. Statist, 22, 326–339.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Peking Uni., China

    Z. Geng, F. Tao & K. Wan

  2. Soka Uni., Japan

    Ch. Asano

  3. Kurashiki Uni. of Sci. & Arts, Japan

    M. Ichimura & M. Kuroda

Authors
  1. Z. Geng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. F. Tao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ch. Asano
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Ichimura
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Kuroda
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Departament d’Estadística i Investigació Operativa, Universitat Politécnica de Catalunya, Avd. Diagonal, 647, E-08028, Barcelona, España

    Albert Prat

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Physica-Verlag Heidelberg

About this paper

Cite this paper

Geng, Z., Tao, F., Wan, K., Asano, C., Ichimura, M., Kuroda, M. (1996). Partial Imputation Method in the EM Algorithm. In: Prat, A. (eds) COMPSTAT. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-46992-3_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-46992-3_30

  • Publisher Name: Physica-Verlag HD

  • Print ISBN: 978-3-7908-0953-4

  • Online ISBN: 978-3-642-46992-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation