gden                   package:sna                   R Documentation

_F_i_n_d _t_h_e _D_e_n_s_i_t_y _o_f _a _G_r_a_p_h

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

     `gden' computes the density of graph `g' in stack `dat', adjusting
     for the type of graph in question.

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

     gden(dat, g=NULL, diag=FALSE, mode="digraph")

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

     dat: Data array to be analyzed.  By assumption, the first
          dimension of the array indexes the graph, with the next two
          indexing the actors.  If `dat' is a matrix, `g' will be
          ignored. 

       g: Integer indicating the index of the graphs for which the
          density is to be calculated.  If `g==NULL' (the default),
          density is calculated for all graphs in `dat'. 

    diag: Boolean indicating whether or not the diagonal should be
          treated as valid data.  Set this true if and only if the data
          can contain loops.  `diag' is `FALSE' by default. 

    mode: String indicating the type of graph being evaluated. 
          "digraph" indicates that edges should be interpreted as
          directed; "graph" indicates that edges are undirected. 
          `mode' is set to "digraph" by default. 

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

     The density of a graph is here taken to be the sum of tie values
     divided by the number of possible ties (i.e., an unbiased
     estimator of the graph mean); hence, the result is interpretable
     for valued graphs as the mean tie value.  The number of possible
     ties is determined by the graph type (and by `diag') in the usual
     fashion.

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

     The graph density

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

     Carter T. Butts ctb@andrew.cmu.edu

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

     Wasserman, S., and Faust, K.  (1994).  ``Social Network Analysis:
     Methods and Applications.''  Cambridge: Cambridge University
     Press.

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

     #Draw three random graphs
     dat<-rgraph(10,3)
     #Find their densities
     gden(dat)

