Assumption-Based Reasoning with General Gaussian Linear Systems
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.
KeywordsUnknown Parameter Conditional Distribution Random Perturbation Previous Chapter Linear Manifold
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