1. A method of developing a corner model for a nonlinear system, comprising the steps of: determining whether an express functional relationship F between at least one-of I performance targets vs. a plurality of statistical model parameters (x 1 , x 2 ,. .. , x m , y 1 , y 2. .. , y N ) is known; deciding, when an express functional relationship between said at least one of I performance targets vs. the plurality of statistical model parameters is known, whether the express functional relationship is linear or nonlinear; when the express functional relationship between said at least one of I performance targets vs. the plurality of statistical model parameters has a non-linear order, expressing the functional relationship between said at least one of I performance targets vs. the plurality of statistical models as a fraction by identifying a numerator and a denominator for said functional relationship; using a set of chosen functions H i (x 1 , x 2 ,. .. , x m , y 1 , y 2. .. , y N ) i=1, 2,. .. I, to decrease the order of the nonlinear functional relationship and to determine a corner model solution for the nonlinear functional relationship; and using one or more hardware processing units, implementing a corner model generating program, to perform the steps of identifying a numerator and a denominator for said functional relationship, and using the set of chosen functions H i to decrease the order of the nonlinear functional relationship.