node                  package:deal                  R Documentation

_R_e_p_r_e_s_e_n_t_a_t_i_o_n _o_f _n_o_d_e_s

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

     An important part of a 'network' is the list of nodes. The nodes
     summarize the local properties of a node, given the parents of the
     node.

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

     node (idx,parents,type="discrete",name=paste(idx),
                      levels=2,levelnames=paste(1:levels),position=c(0,0)) 
     ## S3 method for class 'node':
     print (x,filename=NA,condposterior=TRUE,condprior=TRUE,...) 
     ## S3 method for class 'node':
     plot (x,cexscale=10,notext=FALSE,...)
     nodes(nw)
     value <- nodes(nw)

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

       x: an object of class 'node'.

 parents: a numeric vector with indices of the parents of the node.

     idx: an integer, which gives the index of the node (the column
          number of the corresponding data frame).

    type: a string, which gives the type of the node. Either
          '"discrete"' (for factors) or '"continuous"' (for numeric).

    name: a string, which gives the name used when plotting and
          printing. Defaults to the column  name in the data frame.

  levels: an integer. If 'type' is '"discrete"', this is the number of
          levels for the discrete variable.

levelnames: if 'type' is '"discrete"', this is a vector of strings
          (same length as 'levels') with the names of the levels. If
          'type' is '"continuous"', the argument is ignored.

position: a numeric vector with coordinates where the node should
          appear in the  plot. Usually set by 'network' and
          'drawnetwork'.

      nw: an object of class 'network'.

   value: a list of elements of class 'node'.

filename: a string or 'NA'. If not 'NA', output is printed to a file.

condprior: a logical. If 'TRUE', the conditional prior is printed, see
          'conditional'.

condposterior: a logical. If 'TRUE', the conditional posterior is
          printed, see 'learn'.

cexscale: a numeric. Scale parameter to set the size of the nodes.

  notext: a logical. If 'TRUE', no text is displayed in the nodes on
          the plot.

     ...: additional plot arguments.

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

     The operations on a node are typically done when operating on a
     'network', so these functions are not to be called directly. 

     When a network is created with 'network', the nodes in the
     nodelist are created using the 'node' procedure.

     Local probability distributions are added as the property 'prob'
     to each node using 'prob.node'. If the node is continuous, this is
     a numeric vector with  the conditional variance and the
     conditional regression coefficients arising from a regression on
     the continuous parents, using data. If the node has discrete
     parents, 'prob' is a matrix with a row for each configuration of
     the discrete parents. If the node is discrete, 'prob' is a
     multiway array which gives the conditional probability
     distribution for each configuration of the discrete parents. The
     generated 'prob' can be replaced to match the prior information
     available.

     'nodes' gives the list of nodes of a network. 'localprob' gives
     the probability distribution for each node in the network.

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

     The 'node' creator function returns an object of class 'node',
     which is a list with the following  elements (properties), 

     idx: an integer. A unique index for this node. It MUST correspond
          to the column index of the variable in the data frame.

    name: a string. The printed name of the node.

    type: a string. Either '"continuous"' or '"discrete"'.

  levels: an integer. If the node is of type '"discrete"', this integer
          is the  number of levels of the node.

levelnames: if 'type' is '"discrete"', this is a vector of strings
          (same length as 'levels') with the names of the levels. If
          'type' is '"continuous"', the node does not have this
          property.

 parents: a vector of indices of the parents to this node. It is best
          to manage this vector using the 'insert' function.

    prob: a numeric vector, matrix or multiway array, giving the
          initial probability distribution. If the node is discrete,
          'prob' is a multiway array. If the node is continuous, 'prob'
          is a matrix with one row for each configuration of the
          discrete parents, reducing to a vector if the node has no
          discrete parents.

condprior: a list, generated by 'conditional' giving the parameter
          priors deduced from 'jointprior' using the master prior
          procedure (see 'localmaster'). 

condposterior: a list, which gives the parameter posteriors obtained
          from 'learnnode'.

  loglik: a numeric giving the log likelihood contribution for this
          node, calculated in 'learnnode'.

 simprob: a numeric vector, matrix or multiway array similar to 'prob',
          added by 'makesimprob' and used by 'rnetwork'.

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

     Susanne Gammelgaard Bttcher alma@math.aau.dk, 
      Claus Dethlefsen cld@rn.dk.

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

     Further information about *deal* can be found at:
      <URL: http://www.math.aau.dk/~dethlef/novo/deal>.

