Few Group Collapsing of Covariance Matrix Data Based on a Conservation Principle

A new algorithm for a rigorous collapsing of covariance data is proposed, derived, implemented, and tested. The method is based on a conservation principle that allows the uncertainty calculated in a fine group energy structure for a specific integral parameter, using as weights the associated sensitivity coefficients, to be preserved at a broad energy group structure.