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:

     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

