Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more. 
Home Multivariate Data Basic Knowledge Selection of Variables Survey  
See also: survey on variable selection, chance correlation, crossvalidation, Variable Selection  Pruning, Variable Selection  Forward Selection  
Variable Selection  Introduction
Sometimes a large number of independent variables, X_{i},
is available for a given modeling problem, and not all of these predictor
variables may contribute equally well to the explanation of the predicted
variable Y. Some of the independent variables may not contribute at all
to the model. Thus we have to select from these variables to obtain a model
which contains as little variables as possible while still being the "best"
model. In principle, all possible combinations of independent variables
should be tried for calculating a suitable model. This could turn out to
be a formidable task, even if high performance computers are available.
Besides the practicability of this approach, there are also several theoretical
considerations which should be taken into account:
Using all possible subsets of variables:


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