A Mathematical Theory of Arguments for Statistical Evidence

1. The Theory of Generalized Functional Models.- 2. The Plausibility and Likelihood Functions.- 3. Hints on Continuous Frames and Gaussian Linear Systems.- 4. Assumption-Based Reasoning with Classical Regression Models.- 5. Assumption-Based Reasoning with General Gaussian Linear Systems.- 6. Gaussian Hints as a Valuation System.- 7. Local Propagation of Gaussian Hints.- 8. Application to the Kaiman Filter.- References.