plotR2              package:pcaMethods              R Documentation

_R_2 _p_l_o_t (_s_c_r_e_e_p_l_o_t) _f_o_r _P_C_A

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

     Plot the R2 of the principal components to get an idea of their
     importance. Note though that the standard screeplot shows the
     standard deviations for the PC's this method shows the R2 values
     which empirically shows the importance of the PC's and is thus
     applicable for any PCA method rather than just SVD based PCA.

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

     plotR2(object, nPcs=object@nPcs, type = c("barplot", "lines"), main = deparse(substitute(object)), ...)

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

  object: 'pcaRes' The pcaRes object.

    nPcs: 'numeric' The amount of PC's to consider.

    type: 'character' Barplot or line plot

    main: 'character' The main label of the plot

     ...: Passed on to 'screeplot'

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

     None, used for side effect.

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

     Henning Redestig <redestig[at]mpimp-golm.mpg.de

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

     screeplot

