

orlm(MASS)                                   R Documentation

_F_i_t _R_o_b_u_s_t _L_i_n_e_a_r _R_e_g_r_e_s_s_i_o_n _M_o_d_e_l

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

     Fits a robust linear regression model, using an M-esti-
     mator with Huber's psi function.

_U_s_a_g_e_:

     orlm(formula, data, weights, subset, na.action,
          model=FALSE, k=1.345, sw=1000, ...)

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

 formula: a formula object, with the response on the left of
          a `~' operator, and the terms, separated by `+'
          operators, on the right.

    data: an optional `data.frame' in which to interpret the
          variables named in the formula, or in the `subset'
          and the `weights' argument.

 weights: optional weights; if supplied, the algorithm fits
          to minimize the sum of the weights multiplied into
          the squared residuals.  The weights must be
          strictly positive.

  subset: optional expression saying that only a subset of
          the rows of the data should be used in the fit.

na.action: a missing-data filter function, applied to the
          `model.frame', after any subset argument has been
          used.

   model: flag to control what is returned.  If this is
          `TRUE', then the model frame is returned.  `X' and
          `y' are always returned.

       k: The control value for Winsorizing. The default
          gives 95% efficiency at the normal.

      sw: switch to Huber proposal 2 scale at iteration `sw'
          and beyond.

     ...: additional arguments for the fitting routines.
          The most likely one is `maxit', which sets the
          iteration limit, by default 20.

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

     The fit uses Huber's M-estimator, and initially uses
     the median absolute deviation scale estimate based on
     the residuals. This can be changed to Huber's proposal
     2 after `sw' iterations.

     Generic functions such as `print' and `summary' have
     methods to show the results of the fit.

_V_a_l_u_e_:

     an object of class `rlm' representing the fit, inherit-
     ing from `lm'.  This has all the components of an `lm'
     object, plus `k,' the scale `s' and `conv' which is a
     vector monitoring the convergence.

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

     `rlm'

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

     data(phones)
     attach(phones)
     res <- orlm(calls ~ year)
     print(res)

     data(stackloss)
     rlm(stack.loss ~ stack.x)

