coefplot                 package:pls                 R Documentation

_P_l_o_t _R_e_g_r_e_s_s_i_o_n _C_o_e_f_f_i_c_i_e_n_t_s _o_f _P_L_S_R _a_n_d _P_C_R _m_o_d_e_l_s

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

     Function to plot the regression coefficients of an 'mvr' object.

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

     coefplot(object, ncomp = object$ncomp, separate = FALSE, cumulative = TRUE,
              intercept = FALSE, nCols, nRows, type = "l", ...)

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

  object: an 'mvr' object.  The fitted model.

   ncomp: integer vector.  The number of components to include.  If
          'length(ncomp) > 1', coefficients for each model size is
          plotted.

separate: logical.  If 'TRUE', coefficients for different model sizes
          are blotted in separate plots.

cumulative: logical.  Whether cumulative (the default) or individual
          coefficients for each component should be plotted.  See
          'coef.mvr' for details.

intercept: logical.  Whether coefficients for the intercept should be
          plotted.  Ignored if 'cumulative = FALSE'.  Defaults to
          'FALSE'.  See 'coef.mvr' for details.

nCols, nRows: integer.  The number of coloumns and rows the plots will
          be laid out in.  If not specified, 'coefplot' tries to be
          intelligent.

    type: character.  What type of plot to make.  Defaults to '"l"'
          (lines).  See 'plot' for details.

     ...: Further arguments sent to the underlying plot functions.

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

     'coefplot' handles multiple responses by making one plot for each
     response.  If 'separate' is 'TRUE', separate plots are made for
     each combination of model size and response.  The plots are laid
     out in a rectangular fashion.

     The function can also be called through the 'mvr' plot method by
     specifying 'plottype = "coefficients"'.

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

     Ron Wehrens and Bjrn-Helge Mevik

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

     'mvr', 'plot.mvr', 'coef.mvr', 'plot'

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

     data(NIR)
     mod.nir <- plsr(y ~ X, ncomp = 8, data = NIR)
     ## Not run: 
     coefplot(mod.nir, ncomp = 1:6)
     plot(mod.nir, plottype = "coefficients", ncomp = 1:6) # Equivalent to the previous
     ## End(Not run)

     data(sensory)
     mod.sens <- plsr(Quality ~ Panel, ncomp = 4, data = sensory)
     ## Not run: plot(mod.sens, ncomp = 2:4, separate = TRUE)

