nlmer-class               package:lme4               R Documentation

_R_e_p_r_e_s_e_n_t_a_t_i_o_n _o_f _a _N_o_n_l_i_n_e_a_r _M_i_x_e_d _M_o_d_e_l

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

     The 'lmer' class is a representaiton of nonlinear mixed model
     using sparse matrices.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form 'new("nlmer", ...)'
     or, more commonly via the 'nlmer' function.

_S_l_o_t_s:

     '_e_n_v': An environment (of class '"environment"') created for the
          evaluation of the nonlinear model function.

     '_m_o_d_e_l': The nonlinear model function as an object of class
          '"call"'.

     '_f_r_a_m_e': The model frame for the model, as an object of class
          '"data.frame"'.

     '_p_n_a_m_e_s': Names of the parameters in the nonlinear model (class
          '"character"').

     '_c_a_l_l': The matched call to the function that created the object.
          (class '"call"'). 

     '_f_l_i_s_t': The list of grouping factors for the random effects.

     '_X_t': Sparse model matrix (class '"dgCMatrix"') for the fixed
          effects.

     '_Z_t': Sparse model matrix (class '"dgCMatrix"') for the random
          effects.

     '_y': The response vector (class '"numeric"').

     '_w_e_i_g_h_t_s': Numeric weights vector. This may be of length zero (0)
          indicating unit weights.

     '_c_n_a_m_e_s': a list of character vectors of column names of the
          random-effects variance-covariance matrix associated with
          each grouping factor and the fixed-effects model matrix.

     '_G_p': integer vector of group pointers within the random effects
          and the rows of the transposed model matrix in the 'Zt' slot.
           The elements of 'Gp' are the 0-based index of the first
          element corresponding to each grouping factor.  Thus the
          first element is always 0.  The last element is the total
          length of the random effects vector (also the total number of
          rows in the matrix in the 'Zt' slot).

     '_d_i_m_s': A named integer vector of dimensions.

     '_S_T': A list of S and T factors in the TSST' Cholesky
          factorization of the relative variance matrices of the random
          effects associated with each grouping factor.  The unit lower
          triangular matrix T and the diagonal matrix S are stored as a
          single matrix whose diagonal elements determine S while the
          subdiagonal elements determine the non-trivial elements of T.

     '_V_t': A sparse matrix (of class  '"dgCMatrix"') containing the
          transpose of V=ZTS.

     '_L': The Cholesky decomposition (class '"CHMfactor"') of V'V+I.

     '_m_u': A numeric vector of predicted values from the model with an
          attibute '"gradient"', the gradient matrix.

     '_M_t': The derivative of 'mu' with respect to 'uvec' stored as a
          sparse matrix (class '"dgCMatrix"').

     '_d_e_v_i_a_n_c_e': Named numeric vector of containing the deviance
          corresponding to the maximum likelihood (ML) and REML
          criteria and various components.

     '_f_i_x_e_f': Numeric vector of fixed effects.

     '_r_a_n_e_f': Numeric vector of random effects on the original scale.

     '_u_v_e_c': Numeric vector of orthogonal, constant variance random
          effects.

_M_e_t_h_o_d_s:

     _s_h_o_w 'signature(object = "nlmer")'

     _V_a_r_C_o_r_r 'signature(x = "nlmer")': Extract the variances, standard
          deviations and correlations of the random effects.

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

     'nlmer', 'lmer'

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

     showClass("nlmer")

