Answers are grounded in this paper and cite their sources.
Numerous methods of multivariate calibration methods exist with ridge regression, principal component regression, and partial least squares being the most popular methods in analytical chemistry. This mini‐review overviews multivariate calibration and provides a common theme with respect to the bias/variance tradeoff (harmony) and the harmony/parsimony tradeoff for model selection. Other multivariate calibration considerations are briefly reviewed. A few applications are noted.
No takes yet. Share an insight, caveat, or question.
John H. Kalivas (2005) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: