1. A method of generating a predictor model for predicting multivariable outcomes based upon multivariable inputs with consideration of nuisance variables, said method comprising the steps of: a) defining an initial model as Model Zero and inputting Model Zero as column one of a similarity matrix T; b) performing an optimization procedure to solve for matrix values of an a matrix which is a transformation of outcome profiles associated with input profiles; c) calculating a residual matrix E based on the difference between the actual outcome values and the predicted outcome values determined through a product of matrix T and matrix &agr;; d) selecting a row of the a residual matrix e which contains an error value most closely matching a pre-defined error criterion; e) identifying a row from a matrix of the multivariable inputs which corresponds to the selected row from the residual matrix &egr;; f) calculating similarity values between the identified row and each of the rows in the matrix of the multivariable inputs, including the identified row with itself, g) populating the next column of similarity matrix T with the calculated similarity values if it is determined that the identified row is not collinear or nearly collinear with any previously identified row the similarity values for which were used to populate a previous column of similarity matrix T; and h) repeating steps b) through g) until a predefined stopping criterion has been reached.