Coef                  package:VGAM                  R Documentation

_C_o_m_p_u_t_e_s _M_o_d_e_l _C_o_e_f_f_i_c_i_e_n_t_s _a_n_d _Q_u_a_n_t_i_t_i_e_s

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

     'Coef' is a generic function which computes model coefficients
     from objects returned by modelling functions. It is an auxiliary
     function to 'coef' that enables extra capabilities for some
     specific models.

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

     Coef(object, ...)

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

  object: An object for which the computation of other types of model
          coefficients or quantities is meaningful. 

     ...: Other arguments fed into the specific methods function of the
          model. 

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

     This function can often be useful for 'vglm' objects with just an
     intercept term in the RHS of the formula, e.g., 'y ~ 1'. Then
     often this function will apply the inverse link functions to the
     parameters. See the example below.

     For reduced-rank VGLMs, this function can return the *A*, *C*
     matrices, etc.

     For quadratic and additive ordination models, this function can
     return ecological meaningful quantities such as tolerances,
     optima, maxima.

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

     The value returned depends specifically on the methods function
     invoked.

_W_a_r_n_i_n_g:

     This function may not work for _all_ 'VGAM' family functions. You
     should check your results on some artificial data before applying
     it to models fitted to real data.

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

     Thomas W. Yee

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

     Yee, T. W. and Hastie, T. J. (2003) Reduced-rank vector
     generalized linear models. _Statistical Modelling_, *3*, 15-41.

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

     'coef', 'Coef.vlm', 'Coef.rrvglm', 'Coef.qrrvglm'.

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

     set.seed(123)
     nn = 1000
     y = rbeta(nn, shape1=1, shape2=3) # Original scale
     # parameters are estimated on a log scale:
     fit = vglm(y ~ 1, betaff, tr=TRUE, crit="c") # intercept-only model
     coef(fit, matrix=TRUE) #  log scale
     Coef(fit) # On the original scale

