predict.lqs               package:MASS               R Documentation

_P_r_e_d_i_c_t _f_r_o_m _a_n _l_q_s _F_i_t

_D_e_s_c_r_i_p_t_i_o_n:

     Predict from an resistant regression fitted by 'lqs'.

_U_s_a_g_e:

     ## S3 method for class 'lqs':
     predict(object, newdata, na.action = na.pass, ...)

_A_r_g_u_m_e_n_t_s:

  object: object inheriting from class '"lqs"' 

 newdata: matrix or data frame of cases to be predicted or, if 'object'
          has a formula, a data frame with columns of the same names as
          the variables used.  A vector will be interpreted as a row
          vector.  If 'newdata' is missing, an attempt will be made to
          retrieve the data used to fit the 'lqs' object. 

na.action: function determining what should be done with missing values
          in 'newdata'.  The default is to predict 'NA'.

     ...: arguments to be passed from or to other methods.

_D_e_t_a_i_l_s:

     This function is a method for the generic function 'predict()' for
     class 'lqs'. It can be invoked by calling 'predict(x)' for an
     object 'x' of the appropriate class, or directly by calling
     'predict.lqs(x)' regardless of the class of the object.

     Missing values in 'newdata' are handled by returning 'NA' if the
     linear fit cannot be evaluated. If 'newdata' is omitted and the
     'na.action' of the fit omitted cases, these will be omitted on the
     prediction.

_V_a_l_u_e:

     A vector of predictions.

_A_u_t_h_o_r(_s):

     B.D. Ripley

_S_e_e _A_l_s_o:

     'lqs'

_E_x_a_m_p_l_e_s:

     set.seed(123)
     fm <- lqs(stack.loss ~ ., data = stackloss, method = "S", nsamp = "exact")
     predict(fm, stackloss)