varmx.pca.fd

an object of class <code>pca.fd</code> that is produced by function
<code>pca.fd</code>.

pcafd

the number of harmonics or principal components to be
rotated.

nharm

the number of argument values in a fine mesh
used to define the harmonics to be
rotated.

Principal components are often easier to interpret if they are
rotated.  Among the many possible ways in which this rotation can be
defined, the VARIMAX criterion seems to give satisfactory results most
of the time.

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.pca.fd: Rotation of Functional Principal Components with VARIMAX Criterion

Description

Usage

Arguments

Value

See Also