profile.glm               package:MASS               R Documentation

_M_e_t_h_o_d _f_o_r _P_r_o_f_i_l_i_n_g _g_l_m _O_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Investigates the profile log-likelihood function for a fitted
     model of class '"glm"'.

_U_s_a_g_e:

     ## S3 method for class 'glm':
     profile(fitted, which = 1:p, alpha = 0.01, maxsteps = 10,
             del = zmax/5, trace = FALSE, ...)

_A_r_g_u_m_e_n_t_s:

  fitted: the original fitted model object.

   which: the original model parameters which should be profiled. This
          can be a numeric or character vector. By default, all
          parameters are profiled.

   alpha: highest significance level allowed for the profile
          t-statistics.

maxsteps: maximum number of points to be used for profiling each
          parameter.

     del: suggested change on the scale of the profile t-statistics. 
          Default value chosen to allow profiling at about 10 parameter
          values.

   trace: logical: should the progress of profiling be reported?

     ...: further arguments passed to or from other methods.

_D_e_t_a_i_l_s:

     The profile t-statistic is defined as the square root of change in
     sum-of-squares divided by residual standard error with an
     appropriate sign.

_V_a_l_u_e:

     A list of classes '"profile.glm"' and '"profile"' with an element
     for each parameter being profiled.  The elements are data-frames
     with two variables 

par.vals: a matrix of parameter values for each fitted model.

     tau: the profile t-statistics.

_A_u_t_h_o_r(_s):

     Originally, D. M. Bates and W. N. Venables.  (For S in 1996.)

_S_e_e _A_l_s_o:

     'glm', 'profile', 'plot.profile'

_E_x_a_m_p_l_e_s:

     options(contrasts = c("contr.treatment", "contr.poly"))
     ldose <- rep(0:5, 2)
     numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
     sex <- factor(rep(c("M", "F"), c(6, 6)))
     SF <- cbind(numdead, numalive = 20 - numdead)
     budworm.lg <- glm(SF ~ sex*ldose, family = binomial)
     pr1 <- profile(budworm.lg)
     plot(pr1)
     pairs(pr1)

