Skip to main content

Part of the book series: Statistics for Engineering and Information Science ((ISS))

Abstract

The main reason for building a Bayesian network is to estimate the state of certain variables given some evidence. In Chapter 5, we gave methods that made it easy to access P(A | e) for any variable A. However, this may not be sufficient. It may be crucial to establish the joint probability for a set of variables. Section 6.2 gives a general method for calculating P(V | e) for any set V of variables.

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 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer Science+Business Media New York

About this chapter

Cite this chapter

Jensen, F.V. (2001). Bayesian Network Analysis Tools. In: Bayesian Networks and Decision Graphs. Statistics for Engineering and Information Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3502-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-3502-4_6

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4757-3504-8

  • Online ISBN: 978-1-4757-3502-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics