conditional               package:deal               R Documentation

_C_a_l_c_u_l_a_t_e _c_o_n_d_i_t_i_o_n_a_l _d_i_s_t_r_i_b_u_t_i_o_n

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

     From master distribution the conditional distribution of a node
     given the parents is calculated.

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

     conditional.cont(A,mu,nu,rho,phi) 
     conditional(A,master,nw) 
     conditional.disc(A,master) 
     cond.node(node,nw,nw.prior=jointprior(nw)) 

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

      nw: an object of class `network'.

    node: integer, giving the index of the current node.

nw.prior: a list describing parameter priors, generated by
          `jointprior'.

       A: integer, giving the index of the current node.

  master: a list describing the local master, generated by
          `localmaster'.

      mu: numeric vector. Mu is a parameter in the local master.

      nu: numeric. Nu is a parameter in the local master.

     rho: numeric. Rho is a parameter in the local master.

     phi: numeric matrix. Phi is a parameter in the local master.

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

     Used in `learn', which calls `cond.node'. The local master is
     calculated and sent to `conditional' which calls either
     `conditional.cont' or `conditional.disc' depending on the type of
     the node. In each case the `localmaster' is used for calculating
     the conditional distribution of the current node given the
     remaining nodes in the local master.

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

     The node is updated with `condprior' property, consisting of a
     list with components 

     tau: a numeric matrix, giving the unscaled precision matrix of
          regression parameters.

      mu: a numeric vector, giving the mean of the regression
          parameters.

     phi: a numeric, giving a parameter in the distribution of the
          scale parameter.

     rho: a numeric, giving a parameter in the distribution of the
          scale parameter.

   alpha: a numeric matrix with parameters for Dirichlet distribution.

_A_u_t_h_o_r(_s):

     Susanne Gammelgaard Bttcher alma@math.auc.dk, 
     Claus Dethlefsen dethlef@math.auc.dk.

_R_e_f_e_r_e_n_c_e_s:

     Further information about deal can be found at:
     <URL: http://www.math.auc.dk/novo/deal>.

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

     `learn', `localmaster'

