

   SSuupppplleemmeennttaarryy CCoolluummnnss iinn CCoorrrreessppoonnddeennccee AAnnaallyyssiiss

        supplc(a, ca.res)

   AArrgguummeennttss::

          a: data matrix to be projected.  Must have same num-
             ber of rows as matrix which was initially input to
             the correspondence analysis.

     ca.res: the output of a correspondence analysis.  The fol-
             lowing components of this object are used:
             `evals', `rproj' and `cproj'.

   DDeessccrriippttiioonn::

        Using the results of a correspondence analysis, project
        new columns into the factor space.

   VVaalluuee::

        a matrix, projections of the columns of `a' on the cor-
        respondence analysis factors.

   RReeffeerreenncceess::

        See function `ca'.

   SSeeee AAllssoo::

        Correspondence analysis: `ca'.  Supplementary rows and
        columns: `supplr', `supplc'.  Initial data coding:
        `flou', `logique'.  Other functions producing objects
        of class "reddim": `pca', `sammon'.  Other related
        functions: `prcomp', `cancor', `cmdscale'.  Plotting
        tool: `plaxes'.

   EExxaammpplleess::

        cares <- ca(logarray)
        newproj <- supplc(newcols, cares)
        # plot of first and second factors, and of supplementary columns:
        plot(cares$cproj[,1], cares$cproj[,2],type="n")
        text(cares$cproj[,1], cares$cproj[,2])
        points(newproj[,1], newproj[,2])
        # Place additional axes through x=0 and y=0:
        plaxes(cares$cproj[,1], cares$cproj[,2])

