The rotation problem in factor analysis consists in finding an orthogonal transformation of the initial factor loadings so that the rotated loadings have a simple structure that can be easily interpreted. The most popular orthogonal transformations are the quartimax and varimax procedures with...

The Makov Chain Monte Carlo method (MCMC) is often used to generate independent (pseudo) random numbers from a distribution with a density that is known only up to a normalising constant. With the MCMC method it is not necessary to compute the normalising constant (see e.g. Tierney, 1994; Besag,...