Statistical validation of system models

We frequently develop mathematical models of system behavior and sometimes use test data to help identify the parameters of the mathematical model. However, no general purpose technique exists for formally, statistically judging the quality of a model. The paper suggests a formal statistical procedure for the validation of mathematical models of systems when data taken during operation of the system are available. The statistical validation procedure is based on the bootstrap, and it seeks to build a framework where a statistical test of hypothesis can be run to determine whether or not a mathematical model is an acceptable model of a system with regard to user specified measures of system behavior. A numerical example is presented to demonstrate the application of the technique