logtrans                package:MASS                R Documentation

_E_s_t_i_m_a_t_e _l_o_g _T_r_a_n_s_f_o_r_m_a_t_i_o_n _P_a_r_a_m_e_t_e_r

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

     Find and optionally plot the marginal likelihood for alpha for a
     transformation model of the form `log(y + alpha) ~ x1 + x2 + ...'.

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

     logtrans(object, ..., alpha = seq(0.5, 6, by = 0.25) - min(y), 
              plotit = <<see below>>, interp = <<see below>>,
              xlab="alpha", ylab="log Likelihood")

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

  object: Fitted linear model object, or formula defining the
          untransformed model that is `y ~ x1 + x2 + ...'.  The
          function is generic. 

     ...: If `object' is a formula, this argument may specify a data
          frame as for `lm'. 

   alpha: Set of values for the transformation parameter, alpha. 

  plotit: Should plotting be done?  (Default is `TRUE' if a non-null
          device is currently active, else `FALSE'.) 

  interp: Should the marginal log-likelihood be interpolated with a
          spline approximation?   (Default is `TRUE' if plotting is to
          be done and the number of real points is less than 100.) 

    xlab: as for `plot'. 

    ylab: as for `plot'. 

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

     List with components `x' (for alpha) and `y' (for the marginal
     log-likelihood values).

_S_i_d_e _E_f_f_e_c_t_s:

     A plot of the marginal log-likelihood is produced, if requested,
     together with an approximate mle and 95% confidence interval.

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

     Venables & Ripley, Chapter 6.

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

     `boxcox'

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

     data(quine)
     logtrans(Days ~ Age*Sex*Eth*Lrn, data = quine, 
         alpha = seq(0.75, 6.5, len=20), singular.ok = TRUE)

