Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and here for more.

Variable Selection - Principal Approach

In principle there are two methods to select the variables for a multivariate model to be established:

  • select the variables off-line: the variables are selected before the multivariate model is set up. This is simple but may not be efficient if the selection method does not fit the modeling method. Examples: selection by Fisher ratio, or selection according to correlations.




  • select the variables including the modeling method: the variable selection is included in the whole modeling process. This ensures that the variables are selected in a way which gives the best results with the given modeling method. Examples of this approach are stepwise regression, or growing neural networks.



Last Update: 2012-10-08