Factor Rotation in R

There is always a question as what mapping technique that must be used while rotating factors. In fact, rotation is one of the mapping techniques along with other techniques like reflection, projection, scaling, shearing etc.

But it is always common to use rotation as preferred technique compared to other, the reason might be that it is simple to achieve. Rotation again two types, orthogonal and oblique. Which one we need to use for better factor solution? Gorsuch (1983, pp. 203-204) suggests orthogonal rotation if the factors under study are uncorrelated and oblique if the factors are correlated.

There are other studies that suggest the idea of simple structure despite of factor correlations. For instance, Thurstone (1947) proposes 5 rules to achieve simple structure. The rules are as follows (Brown, J. D., 2009): 

1. Each variable should produce at least one zero loading on some factor.
2. Each factor should have at least as many zero loadings as there are factors.
3. Each pair of factors should have variables with significant loadings on one and zero loadings on the other.
4. Each pair of factors should have a large proportion of zero loadings on both factors (if there are say four or more factors total).
5. Each pair of factors should have only a few complex variables. 

So, these two ideas i.e. from Gorsuch and Thurstone, might provide a clue regarding rotation technique. Now let us see how to handle with problem in R.