Selecting which model to use

Depending on the purpose of the data analysis, several different models maybe appropriate. Choosing which model is better is therefore part of the overall validation procedure. For calibration problems, different models can be compared in terms of how well they predict the dependent variables. Sometimes a priori knowledge of the structure of the data is available (e.g., that fluorescence data can be well approximated by a trilinear model), but often this is not the case. If no external information is available on which comparison of different models can be based, other approaches have to be used. In the following, a discussion is given of how to assess the appropriateness of the model based on the mathematical properties of the data and the model. No exact rules will be given, but rather some guidelines that may be helpful for the data analyst. 

SSmod(Tuckerl) SSmod(Tucker3) SSmod(PARAFAC) (7.5) 

Choosing sensory model from fit and cross-validated fit 

Multi-way Analysis With Applications in the Chemical Sciences 

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