predict.lmList             package:nlme             R Documentation

_P_r_e_d_i_c_t_i_o_n_s _f_r_o_m _a_n _l_m_L_i_s_t _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     If the grouping factor corresponding to 'object' is included in
     'newdata', the data frame is partitioned according to the grouping
     factor levels; else, 'newdata' is repeated for all 'lm'
     components. The predictions and, optionally, the standard errors
     for the predictions, are obtained for each 'lm' component of
     'object', using the corresponding element of the partitioned
     'newdata', and arranged into a list with as many components as
     'object', or combined into a single vector or data frame (if
     'se.fit=TRUE').

_U_s_a_g_e:

     ## S3 method for class 'lmList':
     predict(object, newdata, subset, pool, asList, se.fit, ...)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'lmList', representing a list
          of 'lm' objects with a common model. 

 newdata: an optional data frame to be used for obtaining the
          predictions. All variables used in the 'object' model formula
          must be present in the data frame. If missing, the same data
          frame used to produce 'object' is used. 

  subset: an optional character or integer vector naming the 'lm'
          components of 'object' from which the predictions are to be
          extracted. Default is 'NULL', in which case all components
          are used. 

  asList: an optional logical value. If 'TRUE', the returned object is
          a list with the predictions split by groups; else the
          returned value is a vector. Defaults to 'FALSE'. 

    pool: an optional logical value indicating whether a pooled
          estimate of the residual standard error should be used.
          Default is 'attr(object, "pool")'. 

  se.fit: an optional logical value indicating whether pointwise
          standard errors should be computed along with the
          predictions. Default is 'FALSE'. 

     ...: some methods for this generic require additional arguments. 
          None are used in this method.

_V_a_l_u_e:

     a list with components given by the predictions (and, optionally,
     the standard errors for the predictions) from each 'lm' component
     of 'object',  a vector with the predictions from all  'lm'
     components of 'object', or a data frame with columns given by the
     predictions and their corresponding standard errors.

_A_u_t_h_o_r(_s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

_S_e_e _A_l_s_o:

     'lmList', 'predict.lm'

_E_x_a_m_p_l_e_s:

     data(Orthodont)
     fm1 <- lmList(distance ~ age | Subject, Orthodont)
     predict(fm1, se.fit = TRUE)

