reStruct                package:lme4                R Documentation

_C_r_e_a_t_e _a_n _r_e_S_t_r_u_c_t _o_b_j_e_c_t

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

     Create an `reStruct' object from values for its slots.

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

     reStruct(fixed, random, data, weights, REML, nextraCols, analyticHessian)

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

   fixed: a formula of the form `response ~ terms' where `response' is
          an expression for the response and `terms' are one or more
          terms that define the fixed-effects.

  random: a named list of one-sided formulas.  The names in the list
          evaluate to the grouping factors and the right-hand side of
          the formula is an expression for a `pdMat' object that itself
          contains a formula.  The order of the components of the list
          determines the nesting structure in that the second component
          is nested within the first, the third within the second, and
          so on.

    data: a `data.frame' or `model.frame' in which the `fixed' and
          `random' arguments can be evaluated.

 weights: a numeric vector of prior case weights for the observations.
          Defaults to equal weights.

    REML: a `logical' value: if `TRUE' the REML criterion will be used
          for parameter estimation, otherwise the ML criterion will be
          used.

nextraCols: an `integer' giving the number of extra columns to be added
          to the stored matrices.

analyticHessian: a `ilogical' value: if `TRUE' the analytic Hessian of
          the objective can be calculated using the LMEhessian
          function.

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

     An `reStruct' object.

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

     `reStruct-class', `lmeLevel-class'

