Analytical and numerical computation of error propagation of model parameters.

Linear and nonlinear regression analyses based on the least-squares method play a fundamental role in the evaluation of scientific data. A large number of valuable papers have dealt with various applications of the least-squares method in the chemical literature. They, however, usually contain tremendous formulas for computing the error estimates of the estimated parameters. This paper presents a simple numerical solution based on the well-known simplex method to this problem. Elaborate enzyme kinetic data published earlier have been chosen to test the simplex method extended with error estimation. The capability of the numerical method is demonstrated by the revision of the originally calculated error propagation. Our program might prove useful in handling either chemical or biological data. [ABSTRACT FROM AUTHOR]