plotPcs              package:pcaMethods              R Documentation

_P_l_o_t _m_a_n_y _s_i_d_e _b_y _s_i_d_e _s_c_o_r_e_s _X_O_R _l_o_a_d_i_n_g_s _p_l_o_t_s

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

     A function that can be used to visualise many PCs plotted against
     each other

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

     plotPcs(object, pcs=1:object@nPcs, type=c("scores",
     "loadings"), sl=NULL, hotelling=0.95,...)

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

  object: 'pcaRes' a pcaRes object

     pcs: 'numeric' which pcs to plot

    type: 'character' Either "scores" or "loadings" for scores or
          loadings plot respectively

      sl: 'character' Text labels to plot instead of a point, if NULL
          points are plotted instead of text

hotelling: 'numeric' Significance level for the confidence ellipse.
          NULL means that no ellipse is drawn.

     ...: Further arguments to 'pairs' on which this function is based.

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

     Uses 'pairs' to provide side-by-side plots. Note that this
     function only plots scores or loadings but not both in the same
     plot.

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

     None, used for side effect.

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

     Henning Redestig

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

     'prcomp', 'pca', 'princomp', 'slplot'

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

     data(iris)
     pcIr <- pca(iris[,1:4], nPcs=3,  method="svd")
     plotPcs(pcIr, col=as.integer(iris[,4]) + 1)

