biplot3D            package:compositions            R Documentation

_T_h_r_e_e-_d_i_m_e_n_s_i_o_n_a_l _b_i_p_l_o_t_s, _b_a_s_e_d _o_n _p_a_c_k_a_g_e _r_g_l

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

     Plots variables and cases in the same plot, based on a principal
     component analysis.

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

     biplot3D(x,...)
     ## Default S3 method:
     biplot3D(x,y,var.axes=TRUE,col=c("green","red"),cex=c(2,2),
                 xlabs = NULL, ylabs = NULL, expand = 1,arrow.len = 0.1,
                 ...,add=FALSE)
      ## S3 method for class 'princomp':
      biplot3D(x,choices=1:3,scale=1,...,
                 comp.col=par("fg"),comp.labs=paste("Comp.",1:3),
                 scale.scores=lambda[choices]^(1-scale),
                 scale.var=scale.comp, scale.comp=sqrt(lambda[choices]), 
                 scale.disp=1/scale.comp)

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

       x: princomp object or matrix of point locations to be drawn
          (typically, cases)

 choices: Which principal components should be used?

   scale: a scaling parameter like in 'biplot'

scale.scores: a vector giving the scaling applied to the scores

scale.var: a vector giving the scaling applied to the variables

scale.comp: a vector giving the scaling applied to the unit length of
          each component

scale.disp: a vector giving the scaling of the display in the
          directions of the components

comp.col: color to draw the axes of the components

comp.labs: labels for the components

     ...: further plotting parameters as defined in 'rgl.material'

       y: matrix of  second point/arrow-head locations (typically,
          variables)

var.axes: logical, TRUE draws arrows and FALSE points for y

     col: vector/list of two elements the first giving the color/colors
          for the first data set and the second giving color/colors for
          the second data set.

     cex: vector/list of two elements the first giving the size for the
          first data set and the second giving size for the second data
          set.

   xlabs: labels to be plotted at x-locations

   ylabs: labels to be plotted at y-locations

  expand: the relative expansion of the y data set with respect to x

arrow.len: The length of the arrows as defined in 'arrows3D'

     add: logical, adding to existing plot or making a new one?

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

     This "biplot" is a triplot, relating data, variables and principal
     components. The relative scaling of the components is still
     experimental, meant to mimic the behavior of classical biplots.

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

     nothing

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

     K.Gerald v.d. Boogaart <URL: http://www.stat.boogaart.de>

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

     'gsi'

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

     data(SimulatedAmounts)
     pc <- princomp(acomp(sa.lognormals5))
     pc
     summary(pc)
     plot(pc)           #plot(pc,type="screeplot")
     biplot3D(pc)

