Controlling uncertainty in calibration

A rigorous error-in-both variables procedure for linear and nonlinear curve fitting is described, including determination of the variance/covariance matrix of the fitted parameters. The curve parameters are determined by regression according to the maximum-likelihood functional relationship approach. The variance/covariance matrix is calculated by uncertainty propagation from the variances and covariances of the calibration data.