Chemometrics and modeling

Chemometrics is a chemical discipline in which mathematical and statistical techniques are applied to design experiments or to analyze chemical data. An important part of chemometrics is modeling, in which one tries to relate two or more characteristics in such a way that the obtained model represen ts reality as closely as possible. In this article some less known but usef ul regression methods such as orthogonal least squares. inverse and robust regression are introduced and compared with the well-known classical least squares regression method. Genetic algorithms are described as a means of c arrying out feature selection for multivariate regression. Regression metho ds such as principal component regression and partial least squares are int roduced as well as the use of N-way principal components.