

logtrans(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 spec-
          ify 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)

