actorAdjTable          package:CoCiteStats          R Documentation

_C_o_m_p_u_t_e _a_c_t_o_r _s_i_z_e _a_d_j_u_s_t_m_e_n_t _o_n _a _t_w_o _w_a_y _t_a_b_l_e

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

     When two objects are related through a bipartite graph it is
     sometimes appropriate to carry out special adjustments. One of the
     adjustments is called actor size adjustment. In this case the
     counts are adjusted according to how often the objects are
     referenced.

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

     actorAdjTable(twT, eps = 1e-08)

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

     twT: A two way table as produced by 'twowayTable'. 

     eps: A small quantity used to assess approximate equality.

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

     When testing for associations between entities, the social
     networks literature has developed a number of tools to help
     measure such associations.  We can think of genes (actors) as
     being joined by citation in papers (events) and having two genes
     cited in the same paper (equivalent to two actors attending the
     same event) suggests that they are related to each other. 
     However, some genes are cited in many papers and so we might want
     to discount the level of importance, as compared to genes that are
     cited less often. And additionally, some papers cite very many
     genes, and hence typically say less about them than a paper that
     cites rather fewer genes.

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

     An adjusted two way table, with elements named 'u11', 'u12', 'u21'
     and 'u22'.

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

     R. Gentleman

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

     Testing Gene Associations Using Co-citation, by B. Ding and R.
     Gentleman. Bioconductor Technical Report, 2004

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

     'paperLen', 'twowayTable'

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

       tw1 = twowayTable("10", "100", FALSE)
       actorAdjTable(tw1)

