Class modelling by Soft Independent Modelling of Class Analogy: why, when, how? A tutorial

This article contains a comprehensive tutorial on classification by means of Soft Independent Modelling of Class Analogy (SIMCA). Such a tutorial was conceived in an attempt to offer pragmatic guidelines for a sensible and correct utilisation of this tool as well as answers to three basic questions: why employing SIMCA?, when employing SIMCA? and how employing/not employing SIMCA?. With this purpose in mind, the following points are here addressed: i) the mathematical and statistical fundamentals of the SIMCA approach are presented; ii) distinct variants of the original SIMCA algorithm are thoroughly described and compared in two different case -studies; iii) a flowchart outlining how to fine-tune the parameters of a SIMCA model for achieving an optimal performance is provided; iv) figures of merit and graphical tools for SIMCA model assessment are illustrated and v) computational details and rational suggestions about SIMCA model validation are given. Moreover, a novel Matlab toolbox, which encompasses routines and functions for running and contrasting all the aforementioned SIMCA versions is also made available.

Automated summary

This article provides a comprehensive tutorial on the classification method SIMCA, offering pragmatic guidelines for its correct utilization and answering basic questions on why, when, and how to employ SIMCA. The article addresses mathematical and statistical fundamentals, describes different variants of the algorithm, provides a flowchart for model parameter tuning, illustrates model assessment tools, and gives computational details and suggestions for model validation.