profile-methods            package:bbmle            R Documentation

_L_i_k_e_l_i_h_o_o_d _p_r_o_f_i_l_e_s

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

     Create likelihood profiles for a fitted model

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

     ## S4 method for signature 'mle2':
     profile(fitted, which = 1:p, maxsteps = 100,
                         alpha = 0.01, zmax = sqrt(qchisq(1 - alpha/2, p)),
                         del = zmax/5, trace = FALSE, skiperrs=TRUE,
                         std.err, 
                         tol.newmin = 0.001, debug=FALSE, ...)

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

  fitted: A fitted maximum likelihood model of class mle2

   which: a numeric or character vector describing which parameters to
          profile (default is to profile all parameters)

maxsteps: maximum number of steps to take looking for an upper value of
          the negative log-likelihood

   alpha: maximum (two-sided) likelihood ratio test confidence level to
          find

    zmax: maximum value of signed square root of deviance difference to
          find (default value corresponds to a 2-tailed chi-squared
          test at level alpha)

     del: step size for profiling

   trace: (logical) produce tracing output?

skiperrs: (logical) ignore errors produced during profiling?

 std.err: Optional numeric vector of standard errors, for cases when
          the Hessian is badly behaved.  Will be replicated if
          necessary, and NA values will be replaced by the
          corresponding values from the fit summary

tol.newmin: tolerance for diagnosing a new minimum below the minimum
          deviance estimated in initial fit is found

   debug: (logical) debugging output?

     ...: additional arguments (not used)

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

     The profiling process starts out by ...

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

     'profile.mle-class'

