scoreplot            package:pls            R Documentation(latin1)

_P_l_o_t_s _o_f _S_c_o_r_e_s, _L_o_a_d_i_n_g_s _a_n_d _C_o_r_r_e_l_a_t_i_o_n _L_o_a_d_i_n_g_s

_D_e_s_c_r_i_p_t_i_o_n:

     Functions to make scatter plots of scores or correlation loadings,
     and scatter or line plots of loadings.

_U_s_a_g_e:

     scoreplot(object, ...)
     ## Default S3 method:
     scoreplot(object, comps = 1:2, labels, identify = FALSE, type = "p",
               xlab, ylab, ...)
     ## S3 method for class 'scores':
     plot(x, ...)

     loadingplot(object, ...)
     ## Default S3 method:
     loadingplot(object, comps = 1:2, scatter = FALSE, labels,
                 identify = FALSE, type, lty, lwd = NULL, pch, cex = NULL,
                 col, legendpos, xlab, ylab, pretty.xlabels = TRUE, xlim, ...)
     ## S3 method for class 'loadings':
     plot(x, ...)

     corrplot(object, comps = 1:2, labels, radii = c(sqrt(1/2), 1),
              identify = FALSE, type = "p", xlab, ylab, ...)

_A_r_g_u_m_e_n_t_s:

  object: an R object.  The fitted model.

   comps: integer vector.  The components to plot.

 scatter: logical.  Whether the loadings should be plotted as a scatter
          instead of as lines.

  labels: optional.  Alternative plot labels or x axis labels. See
          Details.

   radii: numeric vector, giving the radii of the circles drawn in
          'corrplot'.  The default radii represent 50% and 100%
          explained variance of the X variables by the chosen
          components.

identify: logical.  Whether to use 'identify' to interactively identify
          points.  See below.

    type: character.  What type of plot to make.  Defaults to '"p"'
          (points) for scatter plots and '"l"' (lines) for line plots. 
          See 'plot' for a complete list of types (not all types are
          possible/meaningful for all plots).

     lty: vector of line types (recycled as neccessary).  Line types
          can be specified as integers or character strings (see 'par'
          for the details).

     lwd: vector of positive numbers (recycled as neccessary), giving
          the width of the lines.

     pch: plot character.  A character string or a vector of single
          characters or integers (recycled as neccessary).  See
          'points' for all alternatives.

     cex: numeric vector of character expansion sizes (recycled as
          neccessary) for the plotted symbols.

     col: character or integer vector of colors for plotted lines and
          symbols (recycled as neccessary).  See 'par' for the details.

legendpos: Legend position.  Optional.  Ignored if 'scatter' is 'TRUE'.
           If present, a legend is drawn at the given position. The
          position can be specified symbolically (e.g., 'legendpos =
          "topright"').  This requires R >= 2.1.0.  Alternatively, the
          position can be specified explicitly ('legendpos =
          t(c(x,y))') or interactively ('legendpos = locator()').

xlab,ylab: titles for x and y axes.  Typically character strings, but
          can be expressions or lists.  See 'title' for details.

pretty.xlabels: logical.  If 'TRUE', 'loadingplot' tries to plot the x
          labels more nicely.  See Details.

    xlim: optional vector of length two, with the x limits of the plot.

       x: a 'scores' or 'loadings' object.  The scores or loadings to
          plot.

     ...: further arguments sent to the underlying plot function(s).

_D_e_t_a_i_l_s:

     'plot.scores' is simply a wrapper calling 'scoreplot', passing all
     arguments.  Similarly for 'plot.loadings'.

     'scoreplot' is generic, currently with a default method that works
     for matrices and any object for which 'scores' returns a matrix. 
     The default 'scoreplot' method makes one or more scatter plots of
     the scores, depending on how many components are selected.  If one
     or two components are selected, and 'identify' is 'TRUE', the
     function 'identify' is used to interactively identify points.

     Also 'loadingplot' is generic, with a default method that works
     for matrices and any object where 'loadings' returns a matrix.  If
     'scatter' is 'TRUE', the default method works exactly like the
     default 'scoreplot' method.  Otherwise, it makes a lineplot of the
     selected loading vectors, and if 'identify' is 'TRUE', uses
     'identify' to interactively identify points.  Also, if 'legendpos'
     is given, a legend is drawn at the position indicated.

     'corrplot' works exactly like the default 'scoreplot' method,
     except that at least two components must be selected.  The
     "correlation loadings", i.e. the correlations between each
     variable and the selected components (see References), are plotted
     as pairwise scatter plots, with concentric circles of radii given
     by 'radii'.  Each point corresponds to an X variable.  The squared
     distance between the point and origin equals the fraction of the
     variance of the variable explained by the components in the panel.
      The default 'radii' corresponds to 50% and 100% explained
     variance.

     'scoreplot', 'loadingplot' and 'corrplot' can also be called
     through the plot method for 'mvr' objects, by specifying
     'plottype' as '"scores"', '"loadings"' or '"correlation"',
     respectively.  See 'plot.mvr'.

     The argument 'labels' can be a vector of labels or one of
     '"names"' and '"numbers"'.  

     If a scatter plot is produced (i.e., 'scoreplot', 'corrplot', or
     'loadingplot' with 'scatter = TRUE'), the labels are used instead
     of plot symbols for the points plotted.  If 'labels' is '"names"'
     or '"numbers"', the row names or row numbers of the matrix
     (scores, loadings or correlation loadings) are used.

     If a line plot is produced (i.e., 'loadingplot'), the labels are
     used as x axis labels.  If 'labels' is '"names"' or '"numbers"',
     the variable names are used as labels, the difference being that
     with '"numbers"', the variable names are converted to numbers, if
     possible.  Variable names of the forms '"number"' or '"number
     text"' (where the space is optional), are handled.

     The argument 'pretty.xlabels' is only used when 'labels' is
     specified for a line plot.  If 'TRUE' (default), the code tries to
     use a 'pretty' selection of labels.  If 'labels' is '"numbers"',
     it also uses the numerical values of the labels for horisontal
     spacing.  If one has excluded parts of the spectral region, one
     might therefore want to use 'pretty.xlabels = FALSE'.

_V_a_l_u_e:

     The functions return whatever the underlying plot function (or
     'identify') returns.

_N_o_t_e:

     'legend' has many options.  If you want greater control over the
     appearance of the legend, omit the 'legendpos' argument and call
     'legend' manually.

     Graphical parametres (such as 'pch' and 'cex') can also be used
     with 'scoreplot' and 'corrplot'.  They are not listed in the
     argument list simply because they are not handled specifically in
     the function (unlike in 'loadingplot'), but passed directly to the
     underlying plot functions by '...'.

     The handling of 'labels' and 'pretty.xlabels' in 'coefplot' is
     experimental.

_A_u_t_h_o_r(_s):

     Ron Wehrens and Bjrn-Helge Mevik

_R_e_f_e_r_e_n_c_e_s:

     Martens, H., Martens, M. (2000) Modified Jack-knife Estimation of
     Parameter Uncertainty in Bilinear Modelling by Partial Least
     Squares Regression (PLSR). _Food Quality and Preference_,
     *11*(1-2), 5-16.

_S_e_e _A_l_s_o:

     'mvr', 'plot.mvr', 'scores', 'loadings', 'identify', 'legend'

_E_x_a_m_p_l_e_s:

     data(yarn)
     mod <- plsr(density ~ NIR, ncomp = 10, data = yarn)
     ## These three are equivalent:
     ## Not run: 
     scoreplot(mod, comps = 1:5)
     plot(scores(mod), comps = 1:5)
     plot(mod, plottype = "scores", comps = 1:5)

     loadingplot(mod, comps = 1:5)
     loadingplot(mod, comps = 1:5, legendpos = "topright") # With legend
     loadingplot(mod, comps = 1:5, scatter = TRUE) # Plot as scatterplots

     corrplot(mod, comps = 1:2)
     corrplot(mod, comps = 1:3)
     ## End(Not run)

