fwdsco                package:forward                R Documentation

_F_o_r_w_a_r_d _S_e_a_r_c_h _T_r_a_n_s_f_o_r_m_a_t_i_o_n _i_n _L_i_n_e_a_r _R_e_g_r_e_s_s_i_o_n

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

     This function applies the forward search approach to the Box-Cox
     transformation of response in linear regression models.

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

     fwdsco(formula, data, nsamp = "best", lambda = c(-1, -0.5, 0, 0.5, 1), 
            x = NULL, y = NULL, intercept = TRUE, na.action, trace = TRUE)

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

 formula: a symbolic description of the model to be fit. The details of
          the model are the same as for lm.

    data: an optional data frame containing the variables in the model.
          By default the variables are taken from the environment from
          which the function is called.

   nsamp: the initial subset for the forward search in linear
          regression is found by fitting the regression model with the
          R function lmsreg (in package `'lqs''). This argument allows
          to control how many subsets areused in the Least  Median of
          Squares regression. The choices are: the number of samples or
          `"best"' (the default) or `"exact"' or `"sample"'. For
          details see help(lmsreg).

  lambda: a vector (or a single numerical value) of lambda values for
          the response transformation.

       x: A matrix of predictors values (if no formula is provided).

       y: A vector of response values (if no formula is provided).

intercept: Logical for the inclusion of the intercept (if no formula is
          provided).

na.action: a function which indicates what should happen when the data
          contain `NA's. The default is set by the `na.action' setting
          of `options', and is `na.fail' if that is unset. The default
          is `na.omit'.

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

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

     The function returns an object of class `"fwdsco"' with the
     following components: 

    call: the matched call.

Likelihood: a ((n-p+1) x n.lambda) matrix of likelihood values.

ScoreTest: a ((n-p+1) x n.lambda) matrix of score test statistic
          values.

    Unit: a list with an element for each lambda values. Each element
          provides a matrix of units added (to a maximum of 5 units) at
          each step of the forward search.

   Input: a list with n, p and the vector of lambda values used.

       x: The design matrix.

       y: The vector for the response.

_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
     4.

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

     'summary.fwdsco', 'plot.fwdsco', 'fwdlm', 'fwdglm'.

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

     data(wool)
     mod <- fwdsco(y ~ x1 + x2 + x3, data = wool)
     summary(mod)
     plot(mod, plot.mle=FALSE)
     plot(mod, plot.Sco=FALSE, plot.Lik=TRUE)

