pdIdnot                 package:mgcv                 R Documentation

_O_v_e_r_f_l_o_w _p_r_o_o_f _p_d_M_a_t _c_l_a_s_s _f_o_r _m_u_l_t_i_p_l_e_s _o_f _t_h_e _i_d_e_n_t_i_t_y _m_a_t_r_i_x

_D_e_s_c_r_i_p_t_i_o_n:

     This set of functions is a modification of the  'pdMat' class
     'pdIdent' from library 'nlme'. The modification is to replace the
     log parameterization used in 'pdMat' with a 'notLog2'
     parameterization, since the latter avoids indefiniteness in the
     likelihood and associated convergence problems: the parameters
     also relate to variances rather than standard deviations, for
     consistency with the 'pdTens' class. The functions are
     particularly useful for working with Generalized Additive Mixed
     Models where variance parameters/smoothing parameters can be very
     large or very small, so that overflow or underflow can be a
     problem.

     These functions would not normally be called directly, although
     unlike the  'pdTens' class it is easy to do so.

_U_s_a_g_e:

     pdIdnot(value = numeric(0), form = NULL, 
            nam = NULL, data = sys.frame(sys.parent()))

_A_r_g_u_m_e_n_t_s:

   value: Initialization values for parameters. Not normally used.

    form: A one sided formula specifying the random effects structure. 

     nam: a names argument, not normally used with this class.

    data: data frame in which to evaluate formula.

_D_e_t_a_i_l_s:

     The following functions are provided: 'Dim.pdIndot',
     'coef.pdIdnot', 'corMatrix.pdIdnot',  'logDet.pdIdnot',
     'pdConstruct.pdIdnot', 'pdFactor.pdIdnot', 'pdMatrix.pdIdnot',
     'solve.pdIdnot', 'summary.pdIdnot'. (e.g. 'mgcv:::coef.pdIdnot' to
     access.)

     Note that while the 'pdFactor' and 'pdMatrix' functions return the
     inverse of the scaled random  effect covariance matrix or its
     factor, the 'pdConstruct' function is initialised with estimates
     of the  scaled covariance matrix itself.

_V_a_l_u_e:

     A class 'pdIdnot' object, or related quantities. See the 'nlme'
     documentation for further details.

_A_u_t_h_o_r(_s):

     Simon N. Wood simon.wood@r-project.org

_R_e_f_e_r_e_n_c_e_s:

     Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and
     S-PLUS. Springer

     The 'nlme' source code.

     <URL: http://www.maths.bath.ac.uk/~sw283/>

_S_e_e _A_l_s_o:

     'te', 'pdTens', 'notLog2', 'gamm'

_E_x_a_m_p_l_e_s:

     # see gamm