On Wed, 26 Apr 2000, Barry Cooke wrote:
> How does one rotate the loadings from a principal component analysis?
> Help on function prcomp() from package mva mentions rotation:
>
> Arguments
>
> retx a logical value indicating whether the rotated
> variables should be returned.
>
> Values
>
> rotation the matrix of variable loadings (i.e., a matrix
> whose olumns contain the eigenvectors). The
> function princomp returns this in the element
> loadings.
>
> x if retx is true the value of the rotated data
> (the data multiplied by the rotation matrix)
> is returned.
>
> but it is unclear to me exactly how the rotation is to be done.
You are being confused by prcomp's S-compatible notation. All PCAs are a
`rotation' of the coordinate system to a basis in which the first component
has maximum variance, the next has maximal variance subject to
uncorrelatedness with the first etc.
> For instance how would one specify a varimax rotation? Or are
> loadings, by default, rotated by the varimax method in prcomp()?
>
> MASS v2 describes the function rotate() on p. 409-410; however R
> complements does not cover this. A search of CRAN indicates Peter
> Ho <peter at esb.ucp.pt> asked the same question Sept 29, 1999, but
> I found no reply.
There is no code to do this in R that I know of. Rotation in the sense
you are describing it belongs with factor analysis, and that is not
currently implemented in R. Indeed `loadings' is FA notation applied to
PCA, and this subject is bedevilled with confusion between the two.
In my view most of the rotation criteria only make sense for FA.
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272860 (secr)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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