A cluster-based method for constructing sparse principal components is proposed. The method initially forms clusters of variables, using a new clustering approach called the semi-partition, in two steps. First, the variables are ordered sequentially according to a criterion involving the...

The independent exploratory factor analysis method is introduced for recovering independent latent sources from their observed mixtures. The new model is viewed as a method of factor rotation in exploratory factor analysis (EFA). First, estimates for all EFA model parameters are obtained...