Use Of Prior Knowledge Research Articles

Summaries

Abstract : A unified approach for the estimation of signals in multiple noise is given. In the general form of the method the authors allow for several signals to be estimated simultaneously. It is possible to use prior knowledge of the signal. Existing methods fall out as special cases as the authors simplify their model. The large sample statistical properties are studied and it is proved that use of prior knowledge is essential for consistent estimates.

Bayes's Theorem and the Use of Prior Knowledge in Regression Analysis

Bayes's Theorem and the Use of Prior Knowledge in Regression Analysis

Bayes's theorem and the use of prior knowledge in regression analysis

Abstract : A Bayesian approach to the problem of integration prior information into the analysis of the normal regression model was adopted. A reinterpretation of the ''mixed'' estimaticedure of Theil and Goldberger was provided with an assumption. It was shown that the posterior distribution of beta takes the form of a product of multivariate normal and multivariate t distributions. What may be regarded as a generalization of Fisher's work on the problem of making inferences when samples are drawn from two normal populations with common mean and unequal variances was obtained. In this case, it was shown that the posterior dis tribution of beta is in the form of the product of two multivariate t distributions.