Skip to main content

Multi-Party Inference and Uncongeniality

  • Reference work entry
  • First Online:
International Encyclopedia of Statistical Science
  • 140 Accesses

Life is more complicated when you have three uncongenial models involved.”

The Multi-Party Inference Reality

Much of the statistical inference literature uses the familiar framework of “God’s model versus my model.” That is, an unknown model, “God’s model,” generates our data, and our job is to infer this model or at least some of its characteristics (e.g., moments, distributional shape) or implications (e.g., prediction). We first postulate one or several models, and then use an array of estimation, testing, selection, and refinement methods to settle on a model that we judge to be acceptable – according to some sensible criterion, hopefully pre-determined – for the inference goals at hand, even though we almost never can be sure that our chosen model resembles God’s model in critical ways. Indeed, philosophically even the existence of God’s model is not a universally accepted concept, just as theologically the existence of God is not an unchallenged notion.

Whether one does or does...

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 1,100.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 549.99
Price excludes VAT (USA)
  • Durable hardcover 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

References and Further Reading

  • Box GEP, Tiao GC (1973) Bayesian inference in statistical analysis. Wiley, New York

    MATH  Google Scholar 

  • Gelman AE, Meng X-L (1996) Model checking and model improvement. In: Gilks W, Richardson S, Spiegelhalter D (eds) Practical Markov chain Monte Carlo, Chapman & Hall, London, pp 189–201

    Google Scholar 

  • Little R, Rubin DB (2002) Statistical analysis with missing data, 2nd edn. Wiley, New York

    MATH  Google Scholar 

  • McCullagh P (2002) What is a statistical model? (with discussion). Ann Stat 30:1225–1310

    MATH  MathSciNet  Google Scholar 

  • Meng X-L (1994) Multiple-imputation inference with uncongenial sources of input (with discussion). Stat Sci 9: 538–573

    Google Scholar 

  • Rubin DB (1987) Multiple imputaiton for nonresponse in surveys. Wiley, New York

    Google Scholar 

  • Xie X, Meng X-L (2010) Multi-party inferences: what happens when there are three uncongenial models involved? Techincal Report, Department of Statistics, Harvard University

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this entry

Cite this entry

Meng, XL. (2011). Multi-Party Inference and Uncongeniality. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_381

Download citation

Publish with us

Policies and ethics