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## Arguments:
## inputs = indices of input variables.
## outputs=indices of output variables.
## useGES = true if algorithm should use GES to determine input-output adjacencies, otherwise uses PC.
## data=the dataset containing variables and observations to run the search on.
## trueInputs=indices of input variables that should be included in the search (can be used to run search over a subset of input variables).
## alphaPC=alpha value used by PC algorithm.
## alphaSober=alpha value used when preforming Sober's step.
## gesDiscount=Penalty used by the FGES algorithm.
## Returns an endogenous latent variable graph (as an edge list).
dm <- function(inputs, outputs, useGES=TRUE, data, trueInputs, alphaPC=.05, alphaSober=.05,
gesDiscount=10, verbose = FALSE, minDiscount=4, java.parameters = NULL){
params <- list()
params$java.parameters <- list()
if(!is.null(java.parameters)){
options(java.parameters = java.parameters)
params$java.parameters <- java.parameters
}
orig.names <- names(data)
new.names <- paste("X", 0:(ncol(data)-1), sep="")
## Need to rename variables as algorithm requires all variables be labeled: X0, X1, etc...
names(data) <-new.names
data <- loadContinuousData(data)
dm <- list()
class(dm) <- "DMSearch"
dm$datasets <- deparse(substitute(df))
## Initiate DMSearch
dm_instance <- .jnew("edu/cmu/tetrad/search/DMSearch")
.jcall(dm_instance, "V", "setInputs", .jarray(as.integer(inputs)))
.jcall(dm_instance, "V", "setOutputs", .jarray(as.integer(outputs)))
.jcall(dm_instance, "V", "setTrueInputs", .jarray(as.integer(trueInputs)))
.jcall(dm_instance, "V", "setData", data)
.jcall(dm_instance, "V", "setVerbose", verbose)
.jcall(dm_instance, "V", "setAlphaSober", as.double(alphaSober))
if(useGES==FALSE){
## Use PC for adj. search.
.jcall(dm_instance, "V", "setAlphaPC", as.double(alphaPC))
}
else{
## Use FGES for adj. search.
.jcall(dm_instance, "V", "setDiscount", as.double(gesDiscount))
.jcall(dm_instance, "V", "setMinDiscount", as.integer(minDiscount))
}
params$useGES <- useGES
params$alphaPC <- alphaPC
params$alphaSober <-alphaSober
params$gesDiscount <- gesDiscount
params$minDiscount <- minDiscount
params$verbose <- verbose
dm$parameters <- params
## Search
dm_graph <- .jcall(dm_instance, "Ledu/cmu/tetrad/graph/Graph;",
"search")
if(!is.null(e <- .jgetEx())){
.jclear()
dm$nodes <- colnames(df)
dm$edges <- NULL
print("Java exception was raised")
print(e)
}else{
V <- extractTetradNodes(dm_graph)
## Restoring original names to nodes.
for(i in 1:length(new.names)){
for(j in 1:length(orig.names)){
if(i==j){
V <- gsub(V,
pattern=paste("^", new.names[j], "$", collapse="", sep=""),
replace=paste(orig.names[i], " ", collapse="", sep=""))
}
}
}
dm$graph <- dm_graph
## Get nodes.
dm$nodes <- V
## extract edges
dm_edges <- extractTetradEdges(dm_graph)
## Restoring original names to edges.
for(i in 1:length(new.names)){
for(j in 1:length(orig.names)){
if(i==j){
dm_edges <- gsub(dm_edges,
pattern=paste("^", new.names[j], " ", collapse="", sep=""),
replace=paste(orig.names[i], " ", collapse="", sep=""))
dm_edges <- gsub(dm_edges,
pattern=paste(" ", new.names[j], collapse="", sep=""),
replace=paste(" ", orig.names[i], collapse="", sep=""))
}
}
}
dm$edges <- dm_edges
}
return(dm)
}
### Example.
##set.seed(123)
##a=rnorm(1000); b=rnorm(1000); c=rnorm(1000)+a+b; d=rnorm(1000)+a+b
##temp <- data.frame(a, b, c, d)
##dm(data=temp, inputs=c(0,1), outputs=c(2,3), useGES=TRUE, trueInputs=c(0,1))
##Should produce following output:
##$nodes
##[1] "L0" "a " "b " "c " "d "
##$edges
##[1] "a --> L0" "b --> L0" "L0 --> c" "L0 --> d"