sla.prcomp            package:RScaLAPACK            R Documentation

_P_r_i_n_c_i_p_a_l _C_o_m_p_o_n_e_n_t_s _A_n_a_l_y_s_i_s (_U_s_i_n_g _S_c_a_L_A_P_A_C_K)

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

     The function 'sla.prcomp' performs a principal components analysis
     on the give data matrix (using 'sla.svd') and returns the results
     as a object of class 'prcomp'.

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

     sla.prcomp(x, retx=TRUE, center=TRUE, scale.=FALSE, tol=NULL, NPROWS, NPCOLS, MB)

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

       x: A numeric matrix which provides the data for the principal
          components analysis.

    retx: a logical value indicating whether the rotated variables
          should be returned.

  center: a logical value indicating whether the variables should be
          shifted to be zero centered.  Alternately, a vector of length
          ncols(x).  The value is passed to 'scale'.

  scale.: a logical value indicating whether the variables should be
          scaled to have unit variance before the analysis takes place.
           The default is 'FALSE' for old compatibility, but in general
          scaling is advisable.  Alternately, a vector of length
          ncols(x).  The value is passed to 'scale'.

     tol: a value indicating the magnitude below which components
          should be omitted.  The default is to omit no components.

  NPROWS: Number of Process Rows in the Process Grid. 

  NPCOLS: Number of Process Cols in the Process Grid. 

      MB: Block Size. 

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

     If the number of processor rows and columns are both zero, one
     processor is used.  If the number of processor rows is nonzero and
     the number of processor columns is zero, then the processor rows
     is taken to be a  number of processors, and a grid is made
     accordingly.

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

    sdev: the standard deviations of the principal components.

rotation: the matrix of variable loadings (i.e., a matrix whose columns
          contain the eigenvectors).

       x: if 'retx' is true, the value of the rotated data (the
          original data multiplied by the 'rotation' matrix).

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

     <URL:
     http://www.google.com/search?q=principal+components+analysis>

     <URL: http://www.netlib.org/scalapack/>

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

     'prcomp' for the normal PCA function.

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

     library(RScaLAPACK)
     data(USArrests)
     sla.prcomp(USArrests, scale=TRUE)

