A device model parameter optimization program, OPTIMA, for extracting parameter values of empirical and/or analytical models most commonly used for VLSI circuit simulation, is described. Such device models often have parameters which are correlated, and some of them could be redundant. OPTIMA can automatically detect redundant model parameter combinations. This not only allows one to extract more meaningful parameters, but also helps in the development of improved physical models with a minimum number of empirical parameters. The parameter redundancy is detected using a statistical confidence region algorithm which can be implemented as a postprocessor to any gradient-based least-squares optimization method. The advantage of the statistical confidence region algorithm in OPTIMA, as applied to MOSFET model parameter extraction, is discussed, using examples from drain and substrate current modeling.>