felix                  package:VGAM                  R Documentation

_F_e_l_i_x _D_i_s_t_r_i_b_u_t_i_o_n _F_a_m_i_l_y _F_u_n_c_t_i_o_n

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

     Estimates the parameter of a Felix distribution by maximum
     likelihood estimation.

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

     felix(link = "elogit", earg = if (link == "elogit") list(min
           = 0, max = 0.5) else list(), method.init=1)

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

link, earg: Link function and extra argument for the parameter. See
          'Links' for more choices and for general information.

method.init: See 'CommonVGAMffArguments'. Valid values are 1, 2, 3 or
          4.

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

     The Felix distribution is an important basic Lagrangian
     distribution. The density function is

  f(y;a) =  (1 / ((y-1)/2)!) * y^((y-3)/2) * a^((y-1)/2) * exp(-ay)

     where y=1,3,5,... and 0 < a < 0.5. The mean is 1/(1-2a) (returned
     as the fitted values). Fisher scoring is implemented.

_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'.

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

     T. W. Yee

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

     Consul, P. C. and Famoye, F. (2006) _Lagrangian Probability
     Distributions_, Boston: Birkhauser.

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

     'dfelix', 'borel.tanner'.

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

     y = 2*rpois(n <- 200, 1) + 1   # Not real data!
     fit = vglm(y ~ 1, felix, trace=TRUE, crit="c")
     coef(fit, matrix=TRUE)
     Coef(fit)
     summary(fit)

