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Assumption-Based Reasoning with General Gaussian Linear Systems

  • Paul-André Monney
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

In this chapter, the assumption-based reasoning principle will be used to draw inferences about the parameter of a given general Gaussian linear system. These inferences will be expressed as Gaussian hints from which degrees of support and degrees of plausibility of hypotheses can be computed.

Keywords

Unknown Parameter Conditional Distribution Random Perturbation Previous Chapter Linear Manifold 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Paul-André Monney
    • 1
  1. 1.Department of StatisticsPurdue UniversityWest LafayetteUSA

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