Map,flowClust-method        package:flowClust        R Documentation

_C_l_u_s_t_e_r _A_s_s_i_g_n_m_e_n_t _B_a_s_e_d _o_n _C_l_u_s_t_e_r_i_n_g _R_e_s_u_l_t_s

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

     This method performs cluster assignment according to the posterior
     probabilities of clustering memberships resulted from the
     clustering (filtering) operations.  Outliers identified will be
     left unassigned by default.

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

     ## S4 method for signature 'flowClust':
     Map(f, rm.outliers=TRUE, ...)

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

       f: Object returned from 'flowClust' or 'filter'.

rm.outliers: A logical value indicating whether outliers will be left
          unassigned or not.

     ...: Further arguments to be passed to or from other methods.

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

     A numeric vector of size N (the number of observations) indicating
     to which cluster each observation is assigned.  Unassigned
     observations will be labelled as 'NA'.

_N_o_t_e:

     Even if 'rm.outliers' is set to 'FALSE', 'NA' may still appear in
     the resultant vector due to the filtered observations; see the
     descriptions about the 'min.count', 'max.count', 'min' and 'max'
     arguments of 'flowClust'.

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

     Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>

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

     Lo, K., Brinkman, R. R. and Gottardo, R. (2008) Automated Gating
     of Flow Cytometry Data via Robust Model-based Clustering.
     _Cytometry A_ *73*, 321-332.

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

     'flowClust', 'filter', 'posterior'

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

     res <- flowClust(iris[,1:4], K=3)
     Map(res)
     Map(res, rm.outliers=FALSE)

