Linear regression with constraints on correlation coefficients
We examine parameter estimation in a linear regression model using prior information about the correlation coefficients of the model inputs and outputs, specified in the form of bounds on the admissible input-output correlations. The solution is reduced to a quadratic programming problem.
scientific article; zbMATH DE number 4013791