posterior             package:flowClust             R Documentation

_V_a_r_i_o_u_s _F_u_n_c_t_i_o_n_s _f_o_r _R_e_t_r_i_e_v_i_n_g _I_n_f_o_r_m_a_t_i_o_n _f_r_o_m _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:

     Various functions are available to retrieve the posterior
     probabilities of clustering memberships z ('posterior'), the
     weights u ('importance'), the uncertainty ('uncertainty'), and
     the estimates of the cluster means and proportions
     ('getEstimates') resulted from the clustering (filtering)
     operation.

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

     posterior(object, assign=FALSE)
     importance(object, assign=FALSE)
     uncertainty(object)
     getEstimates(object)

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

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

  assign: A logical value.  If 'TRUE', only the quantity ('z' for
          'posterior' or 'u' for 'importance') associated with the
          cluster to which an observation is assigned will be returned.
           Default is 'FALSE', meaning that the quantities associated
          with all the clusters will be returned.

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

     These functions are written to retrieve various slots contained in
     the object returned from the clustering operation.  'posterior'
     and 'importance' provide a means to conveniently retrieve
     information stored in 'object@z' and 'object@u' respectively. 
     'uncertainty' is to retrieve 'object@uncertainty', and
     'getEstimates' is to retrieve information stored in 'object@mu'
     (transformed back to the original scale) and 'object@w'.

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

     Denote by K the number of clusters, N the number of observations,
     and P the number of variables.  For 'posterior' and 'importance',
     a matrix of size N x K is returned if 'assign=FALSE' (default). 
     Otherwise, a vector of size N is outputted.  'uncertainty' always
     outputs a vector of size N.  'getEstimates' returns a list with
     two names elements, 'locations' and 'proportions'.  'locations' is
     a matrix of size K x P and contains the estimates of the K mean
     vectors transformed back to the original scale (i.e.,
     'rbox(object@mu, object@lambda)').  'proportions' is a vector of
     size P and contains the estimates of the K cluster proportions.

_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', 'Map'

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

     res <- flowClust(iris[,1:4], K=3)
     posterior(res)
     posterior(res, assign=TRUE)
     importance(res)
     importance(res, assign=TRUE)
     uncertainty(res)
     getEstimates(res)

