lmsglm                package:forward                R Documentation

_F_o_r_w_a_r_d _S_e_a_r_c_h _i_n _G_e_n_e_r_a_l_i_z_e_d _L_i_n_e_a_r _M_o_d_e_l_s

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

     This function computes the Least Median Square robust fit for
     generalized linear models using deviance residuals.

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

     lmsglm(x, y, family, weights, offset, n.samples = 100, max.samples = 200, epsilon = 1e-04, maxit = 50, trace = FALSE)

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

       x: a matrix or data frame containing the explanatory variables.

       y: the response: a vector of length the number of rows of `x'.

  family: a description of the error distribution and link function to
          be used in the model. See `family' for details.

 weights: an optional vector of weights to be used in the fitting
          process.

  offset: optional, a priori known component to be included in the
          linear predictor during fitting.

n.samples: number of good subsets to fit. It can be a numeric value or
          `"all"'.

max.samples: maximal number of subsets to fit. By default is set to
          twice `n.samples'.

 epsilon: positive convergence tolerance epsilon. See 'glm.control' for
          details.

   maxit: integer giving the maximal number of IWLS iterations. See
          'glm.control' for details.

   trace: logical, if 'TRUE' a message is printed for every ten
          iterations completed during the search.

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

     This function is used by  'fwdglm' to select the starting subset
     for the forward search. For this reason, users do not generally
     need to use it.

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

     The function returns a list with the following components: 

     bsb: a vector giving the best subset found

 dev.res: a vector giving the deviance residuals for all the
          observations

 message: a short message about the status of the algorithm

   model: the model provided by `glm.fit' using the units in the best
          subset found

_A_u_t_h_o_r(_s):

     Originally written for S-Plus by: Kjell Konis
     kkonis@insightful.com and Marco Riani mriani@unipr.it 
      Ported to R by Luca Scrucca luca@stat.unipg.it

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

     Atkinson, A.C. and Riani, M. (2000),  _Robust Diagnostic
     Regression Analysis_, First Edition. New York: Springer, Chapter
     6.

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

     'fwdglm', 'fwdlm', 'lmsreg', 'fwdsco'.

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

