box                package:flowClust                R Documentation

_B_o_x-_C_o_x _T_r_a_n_s_f_o_r_m_a_t_i_o_n

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

     This function performs Box-Cox transformation on the inputted data
     matrix.

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

     box(data, lambda)

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

    data: A numeric vector, matrix or data frame of observations. 
          Negative data values are permitted.

  lambda: The transformation to be applied to the data.  If negative
          data values are present, 'lambda' has to be positive.

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

     To allow for negative data values, a slightly modified version of
     the original Box-Cox (1964) is used here.  This modified version
     originated from Bickel and Doksum (1981), taking the following
     form:

            f(y) = ( sgn(y) abs(y)^(lambda) -1 ) / lambda

     When negative data values are involved, the transformation
     parameter, 'lambda', has to be positive in order to avoid
     discontinuity across zero.

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

     A numeric vector, matrix or data frame of the same dimension as
     'data' is returned.

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

     Bickel, P. J. and Doksum, K. A. (1981) An Analysis of
     Transformations Revisited. _J. Amer. Statist. Assoc._ *76*(374),
     296-311.

     Box, G. E. P. and Cox, D. R. (1964) An Analysis of
     Transformations. _J. R. Statist. Soc. B_ *26*, 211-252.

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

     'rbox'

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

     data(rituximab)
     data <- exprs(rituximab)
     summary(data)
     # Transform data using Box-Cox with lambda=0.3
     dataTrans <- box(data, 0.3)
     # Reverse transform data; this should return back to the original rituximab data
     summary(rbox(dataTrans, 0.3))

