deal (version 1.1-2)

autosearch: Autosearch

Description

Greedy search for a network with high networkscore

Usage

autosearch(initnw,data,prior=jointprior(network(data)),maxiter=50,
           trylist= rep(list(NULL),initnw$n),trace=FALSE,
           timetrace=FALSE,smalldf=NA,showban=FALSE,saveall=TRUE)

Arguments

initnw

The initial network from which the search is started.

data

Dataframe used for learning the network, see network.

prior

A joint prior, see jointprior.

maxiter

Maximum search steps in the search algorithm.

trylist

Used internally for reusing learning of nodes, see maketrylist.

trace

If TRUE, plots the networks during search.

timetrace

If TRUE, prints some timing information on the screen.

smalldf

Used for analysing networks with time-varying nodes, see timeslice.

showban

Passed to plot.network.

saveall

If TRUE, all networks explored in the search is returned (memory consuming). Otherwise only the best is returned.

Value

• A list with two elements
• nw
  A networkfamily with all (or the best) tried networks. Duplicate networks have not been removed (use nwfunique).
• trylist
  Updated.

Details

In each step, a list of networks is created with either one extra arrow, one less arrow or with one arrow turned (if a cycle is not generated). The network scores of all the proposal networks are calculated and the network with the highest score is chosen for the next step in the search. If no proposed networks has a higher network score than the previous network, the search is terminated. The returned network list contain all tried networks (depending on the value of saveall).

References

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

See Also

heuristic

Examples

data(rats)
fit       <- network(rats,specifygraph=FALSE,inspect=FALSE)
fit.prior <- jointprior(fit,12)
fit       <- learn(fit,rats,fit.prior)$nw
fit       <- insert(fit,2,1,rats,fit.prior)$nw
fit       <- insert(fit,1,3,rats,fit.prior)$nw
hisc      <- autosearch(fit,rats,fit.prior)$nw
hisc      <- nwfsort(hisc)