scale                  package:base                  R Documentation

_S_c_a_l_i_n_g _a_n_d _C_e_n_t_e_r_i_n_g _o_f _M_a_t_r_i_x-_l_i_k_e _O_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     `scale' is generic function who's default method centers and/or
     scales the columns of a numeric matrix.

_U_s_a_g_e:

     scale(x, center = TRUE, scale = TRUE)

_A_r_g_u_m_e_n_t_s:

       x: a numeric matrix(like object).

  center: either a logical value or a numeric vector of length equal to
          the number of columns of `x'.

   scale: either a logical value or a numeric vector of length equal to
          the number of columns of `x'.

_D_e_t_a_i_l_s:

     The value of `center' determines how column centering is
     performed. If `center' is a numeric vector with length equal to
     the number of columns of `x', then each column of `x' has the
     corresponding value from `center' subtracted from it. If `center'
     is `TRUE' then centering is done by subtracting the column means
     of `x' from their corresponding columns, and if `center' is
     `FALSE', no centering is done.

     The value of `scale' determines how column scaling is performed
     (after centering). If `scale' is a numeric vector with length
     equal to the number of columns of `x', then each column of `x' is
     divided by the corresponding value from `scale'. If `scale' is
     `TRUE' then scaling is done by dividing the (centered) columns of
     `x' by their root-mean-square, and if `scale' is `FALSE', no
     scaling is done.

     The root-mean-square for a column is obtained by computing the
     square-root of the sum-of-squares of the non-missing values in the
     column divided by the number of non-missing values minus one.

_V_a_l_u_e:

     For `scale.default', the centered, scaled matrix.

_S_e_e _A_l_s_o:

     `sweep' which allows centering (and scaling) with arbitrary
     statistics.

_E_x_a_m_p_l_e_s:

     x <- matrix(1:10, nc=2)
     (centered.x <- scale(x, scale=FALSE))
     cov(centered.scaled.x <- scale(x))# all 1

