Patent ID: 6317640
Filing Date: 2001-11-13
Classification: G06F

Abstract:
A method for predictive modeling of a process comprising the steps of:accumulating experimental data associated with a relationship of a particular output parameter and a variance in that output parameter as a plurality of input parameters are varied, the experimental data accumulated at a plurality of data points defining a design space;calculating a mean and standard deviation of the experimental data accumulated for each of the data points;normalizing the experimental data at each of the data points to a common mean and variance;merging the normalized data to create a cumulative distribution function representing an overall shape of the accumulated data;calculating an interpolated mean value and standard deviation value for a new point within the design space using the mean and standard deviation calculated for the data points; andapplying the interpolated mean value and interpolated standard deviation value to the cumulative distribution function to provide a predicted output data distribution for the new point.