deal (version 1.2-4)

drawnetwork: Graphical interface for editing networks

Description

drawnetwork allows the user to specify a Bayesian network through a point and click interface.

Usage

drawnetwork(nw,df,prior,trylist=vector("list",nw$n),
            unitscale=20,cexscale=8,
            arrowlength=.25,nocalc=FALSE,
            yr=c(0,350),xr=yr,...)

inspectprob(nw,unitscale=20,cexscale=8,
            arrowlength=.25,xr=c(0,350),yr=xr,...)

Arguments

nw

an object of class network to be edited.

df

a data frame used for learning the network, see network.

prior

a list containing parameter priors, generated by jointprior.

trylist

a list used internally for reusing learning of nodes, see maketrylist.

cexscale

a numeric passed to plot.network. Measures the scaled size of text and symbols.

arrowlength

a numeric passed to plot.network. Measures the length of the edges of the arrowheads.

nocalc

a logical. If TRUE, no learning procedure is called, see eg. simulation.

unitscale

a numeric passed to plot.network. Scale parameter for chopping off arrow heads.

xr

a numeric vector with two components containing the range on x-axis.

yr

a numeric vector with two components containing the range on y-axis.

...

additional plot arguments, passed to plot.network.

Value

• A list with two elements,
• nw
  an object of class network with the final network.
• trylist
  an updated list used internally for reusing learning of nodes, see maketrylist.

Details

To insert an arrow from node 'A' to node 'B', first click node 'A' and then click node 'B'. When the graph is finished, click 'stop'. To specify that an arrow must not be present, press 'ban' (a toggle) and draw the arrow. This is shown as a red dashed arrow. It is possible to ban both directions between nodes. The ban list is stored with the network in the property banlist. It is a matrix with two columns. Each row is the 'from' node index and the 'to' node index, where the indices are the column number in the data frame. Note that the network score changes as the network is re-learned whenever a change is made (unless nocalc is TRUE). inspectprob draws the network and makes it possible to inspect the prob properties of the nodes by clicking on them. The result is shown in the output window.

References

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

See Also

network

Examples

data(rats)
rats.nw    <- network(rats)
rats.prior <- jointprior(rats.nw,12)
rats.nw    <- learn(rats.nw,rats,rats.prior)$nw

newrat  <- drawnetwork(rats.nw,rats,rats.prior)$nw