deprecated              package:statmod              R Documentation

_D_e_p_r_e_c_a_t_e_d _F_u_n_c_t_i_o_n_s _i_n _s_t_a_t_m_o_d _P_a_c_k_a_g_e

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

     These functions are provided for compatibility with older versions
     of R only, and may be defunct as soon as the next release.

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

     randomizedBlock(formula, random, weights=NULL, only.varcomp=FALSE, data=list(), subset=NULL, contrasts=NULL, tol=1e-6, maxit=50, trace=FALSE)
     randomizedBlockFit(y, X, Z, w=NULL, only.varcomp=FALSE, tol=1e-6, maxit=50, trace=FALSE)

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

     The arguments 'formula', 'weights', 'data', 'subset' and
     'contrasts' have the same meaning as in 'lm'. The arguments 'y',
     'X' and 'w' have the same meaning as in 'lm.wfit'. 

 formula: formula specifying the fixed model.

  random: vector or factor specifying the blocks corresponding to
          random effects.

 weights: optional vector of prior weights.

only.varcomp: logical value, if 'TRUE' computation of standard errors
          and fixed effect coefficients will be skipped

    data: an optional data frame containing the variables in the model.

  subset: an optional vector specifying a subset of observations to be
          used in the fitting process.

contrasts: an optional list. See the 'contrasts.arg' argument of
          'model.matrix.default'.

     tol: small positive numeric tolerance, passed to 'glmgam.fit'

   maxit: maximum number of iterations permitted, passed to
          'glmgam.fit'

   trace: logical value, passed to 'glmgam.fit'. If 'TRUE' then working
          estimates will be printed at each iteration.

       y: numeric response vector

       X: numeric design matrix for fixed model

       Z: numeric design matrix for random effects

       w: optional vector of prior weights

_D_e_t_a_i_l_s:

     'randomizedBlock' and 'randomizedBlockFit' have been renamed to
     'mixedModel2' and 'mixedModel2Fit' respectively.

