cals-methods             package:msbase             R Documentation

_S_i_m_i_l_a_r_i_t_y _b_y _u_s_e_r _d_e_f_i_n_e_d _f_u_n_c_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Compute similarity between two Massvectors using a similarity
     function passed to argument msim

_A_r_g_u_m_e_n_t_s:

     obx: see below in *Methods* section

     oby: see above in *Methods* section

   error: measurement error

     ppm: if 'TRUE' then error in parts per million, in arbitrary units
          otherwise

    msim: similarity function

       p: argument to similarity function

    uniq: if 'TRUE' compute optimal aligmnent

_V_a_l_u_e:

     Scalar, Vector or object of class 'dist'

_M_e_t_h_o_d_s:

     _o_b_x = "_n_u_m_e_r_i_c", _o_b_y = "_n_u_m_e_r_i_c" given two vectors computes
          alignement and similarity using function passed to arguement
          mdist

     _o_b_x = "_M_a_s_s_v_e_c_t_o_r", _o_b_y = "_M_a_s_s_v_e_c_t_o_r" same for 'Massvectors'

     _o_b_x = "_M_a_s_s_v_e_c_t_o_r_l_i_s_t", _o_b_y = "_M_a_s_s_v_e_c_t_o_r" compute similarities
          between 'Massvector' and 'Massvectorlist'

     _o_b_x = "_M_a_s_s_v_e_c_t_o_r_l_i_s_t", _o_b_y = "_N_U_L_L" computes object of class
          'dist' casting the similarities into distances

_A_u_t_h_o_r(_s):

     Witold E. Wolski witek96@users.sourceforge.net

_S_e_e _A_l_s_o:

     'calssim','calsrange'

_E_x_a_m_p_l_e_s:

     data(pldata)
     pl1 <- pldata[[1]]
     pl2 <- pldata[[2]]
     cals(pl1,pl2,error=400,ppm=TRUE,msim=calssim,p=3)
     cals(pl1,pl2,error=400,ppm=TRUE,msim=calsrange)
     tmp <- cals(pldata,NULL,error=400,ppm=TRUE,msim=calssim,p=3)
     plot(hclust(tmp,method="average"))

