Assumption-Based Reasoning with General Gaussian Linear Systems
Paul-André Monney · Contributions to statistics · 2003
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. 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.