rig                   package:VGAM                   R Documentation

_R_e_c_i_p_r_o_c_a_l _I_n_v_e_r_s_e _G_a_u_s_s_i_a_n _d_i_s_t_r_i_b_u_t_i_o_n

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

     Estimation of the parameters of a  reciprocal inverse Gaussian
     distribution.

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

     rig(lmu = "identity", llambda = "loge",
         emu=list(), elambda=list(), imu = NULL, ilambda = 1)

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

lmu, llambda: Link functions  for 'mu' and 'lambda'. See 'Links' for
          more choices.

imu, ilambda: Initial values for 'mu' and 'lambda'. A 'NULL' means a
          value is computed internally.

emu, elambda: List. Extra argument for each of the links. See 'earg' in
          'Links' for general information.

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

     See Jorgensen (1997) for details.

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

     An object of class '"vglmff"' (see 'vglmff-class'). The object is
     used by modelling functions such as 'vglm', and 'vgam'.

_N_o_t_e:

     This distribution is potentially useful for dispersion modelling.

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

     T. W. Yee

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

     Jorgensen, B. (1997) _The Theory of Dispersion Models_. London:
     Chapman & Hall

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

     'simplex'.

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

     y = rchisq(n=100, df=14)    # Not 'proper' data!!
     fit = vglm(y ~ 1, rig, trace=TRUE)
     fit = vglm(y ~ 1, rig, trace=TRUE, eps=1e-9, cri="c")
     summary(fit)

