hllm                 package:gRbase                 R Documentation

_H_i_e_r_a_r_c_h_i_c_a_l _l_o_g-_l_i_n_e_a_r _m_o_d_e_l_s

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

     An implementation of hierarchical log-linear models using the
     framework of 'gRbase'. A model object is defined using 'hllm',
     fitted using 'fit' (which calls 'loglm') and a model search
     performed  using 'stepwise'. The models may be displayed and
     manipulated using the 'gRbase' functions, eg. 'dynamic.Graph'.

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

     hllm(formula = ~.^1, gmData, marginal)

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

 formula: an object of class 'formula'. The right hand side of the
          formula is a list of the generators separated by '+'. A
          generator is specified by variable names with separated by
          '*'. Commonly used models have short hand notations:
          saturated model ('~.^.'), main effects ('~.^1'), all k'th
          order interactions ('~.^k'). 

  gmData: an object of class 'gmData'.

marginal: an optional argument specifying a subset of the variables
          from the 'gmData' object.

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

     'hllm' returns an object of class 'hllm', inheriting from the
     superclass 'gModel'.

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

     Sren Hjsgaard, sorenh@agrsci.dk, 
      Claus Dethlefsen, aas.claus.dethlefsen@nja.dk

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

     'gmData', 'gRfit', 'ggm', 'dynamic.Graph'

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

     data(reinis)
     reinis <- as.gmData(reinis)
     m2 <-
     hllm(~smoke*phys*protein+mental*phys+mental*family+smoke*systol*protein,
     reinis)
     m2 <- fit(m2,engine="loglm")
     ## Not run: dynamic.Graph(m2)

