STATISTICAL CALIBRATION - A REVIEW

This paper reviews the wide variety of approaches to both univariate and multivariate calibration. In particular, in univariate calibration, it considers the classical, inverse, Bayesian and non-parametric approaches together with the approaches via tolerance regions. In multivariate calibration, it considers the ridge regression, multiple linear regression, partial least squares regression and principal components regression approaches together with the Bayesian and profile likelihood approaches. An extensive bibliography is provided.