checkEstimable              package:gnm              R Documentation

_C_h_e_c_k _W_h_e_t_h_e_r _O_n_e _o_r _M_o_r_e _P_a_r_a_m_e_t_e_r _C_o_m_b_i_n_a_t_i_o_n_s _i_n _a _g_n_m _M_o_d_e_l
_a_r_e _I_d_e_n_t_i_f_i_e_d

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

     For each of a specified set of combinations of parameters from a
     'gnm' model, checks numerically whether the combination's estimate
     is invariant to re-parameterization of the model.

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

     checkEstimable(model, coefMatrix, tolerance = 1e-8)

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

   model: a model object of class '"gnm"' 

coefMatrix: numeric: either a vector of length the same as
          'length(coef(model))', or a matrix with that number of rows.
          Coefficients of one or more linear combinations of the
          model's parameters.

tolerance: numeric: a threshold value for detection of
          non-estimability.  

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

     A logical vector of length equal to the number of parameter
     combinations tested; 'NA' where a parameter combination is
     identically zero.

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

     David Firth

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

     'gnm',  'se', 'getContrasts'

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

     data(yaish)
     set.seed(1)

     ## Fit the "UNIDIFF" mobility model across education levels
     unidiff <- gnm(Freq ~ educ:orig + educ:dest +
                    Mult(Exp(educ), orig:dest), family = poisson,
                    data = yaish)

     ## Check whether Mult1.Factor1.educ4 - Mult1.Factor1.educ5 is estimable
     educ4.pos <- grep("Mult1.Factor1.educ4", names(coef(unidiff)))
     checkEstimable(unidiff, c(rep(0, educ4.pos - 1), 1, -1,
                               rep(0, length(coef(unidiff)) - educ4.pos - 1)))
     ## should be TRUE

     ## Check whether Mult1.Factor1.educ4 is estimable
     checkEstimable(unidiff, c(rep(0, educ4.pos - 1), 1, 0,
                               rep(0, length(coef(unidiff)) - educ4.pos - 1)))
     ## should be FALSE -- only *differences* are identified here

