varmx

the matrix to be rotated.  The number of rows is
equal to the number of argument values <code>nx</code> used
in a fine mesh.  The number of columns is the number of
components to be rotated.

amat

either <code>TRUE</code> or <code>FALSE</code>.  If <code>TRUE</code>, the columns of
<code>amat</code> are normalized prior to computing the rotation
matrix.  However, this is seldom needed for functional data.

normalize

The matrix being rotated contains the values of the component
functional data objects computed in either a principal
components analysis or a canonical correlation analysis.
The values are computed over a fine mesh of argument values.

smooth

These functions were developed to support functional data
        analysis as described in Ramsay, J. O. and Silverman, B. W.
        (2005) Functional Data Analysis. New York: Springer.  They were
        ported from earlier versions in Matlab and S-PLUS.  An
        introduction appears in Ramsay, J. O., Hooker, Giles, and
        Graves, Spencer (2009) Functional Data Analysis with R and
        Matlab (Springer). The package includes data sets and script
        files working many examples including all but one of the 76
        figures in this latter book.  Matlab versions of the code and
        sample analyses are no longer distributed through CRAN, as they
        were when the book was published.  For those, ftp from
        http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/
        There you find a set of .zip files containing the functions and
        sample analyses, as well as two .txt files giving instructions for
        installation and some additional information.

varmx: Rotate a Matrix of Component Loadings using the VARIMAX Criterion

Description

Usage

Arguments

Value

Details

See Also