forrwcoa                package:made4                R Documentation

_R_o_w _w_e_i_g_h_t_e_d _C_o_r_r_e_s_p_o_n_d_e_n_c_e _A_n_a_l_y_s_i_s

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

     'dudi.rwcoa' Row weighted COA, calls 'forrwcoa' to perform row
     weighted correspondence analysis.

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

     forrwcoa(df, rowweights = rep(1/nrow(df),nrow(df)))

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

      df: a 'data.frame' containing positive or null values. It should
          not contain missing (NA) values. 

rowweights: a vector of row weights (by default, uniform row weights) 

     ...: further arguments passed to or from other methods ) 

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

     Performs row weighted COA. Calls 'forrwcoa' to calculates weights.

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

     Returns a list of class 'coa', 'rwcoa', and 'dudi' (see 'dudi')

_N_o_t_e:

     In the paper by Culhane et al., 2002, coinertia analysis was
     performed with two COAs, a standard 'COA' and a row weighted COA
     'dudi.rwcoa', on the two gene expression datasets. However it is
     now recommended to perform two non-symmetric COA, instead of two
     COA. This avoids having to force the row weights from one analysis
     on the second.  To perform non-symmetric correspondence coinertia
     analysis, use 'nsc.coinertia'.

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

     Aedin Culhane,  A.B. Dufour

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

     Culhane AC, et al., 2003 Cross platform comparison and
     visualisation of gene expression data using co-inertia analysis. 
     BMC Bioinformatics. 4:59

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

     See Also as 'dudi','dudi.coa','dudi.pca' 'nsc.coinertia'

