R Under development (unstable) (2024-09-06 r87103 ucrt) -- "Unsuffered Consequences"
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> ## Translate amat as describes in amatType to dagitty object
> if(requireNamespace("dagitty")) {
+ library(pcalg)
+ library(dagitty)
+ suppressWarnings(RNGversion("3.5.0"))
+ doExtras <- pcalg:::doExtras()
+ 
+ res <- rep(FALSE, 10)
+ ####################
+ ## Test DAG 1
+ ####################
+ data(gmG)
+ n <- nrow    (gmG8$x)
+ V <- colnames(gmG8$x) # labels aka node names
+ 
+ amat <- wgtMatrix(gmG8$g)
+ amat[amat != 0] <- 1
+ dagitty_dag1 <- pcalg2dagitty(amat,V,type="dag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow=c(1,2))
+ ## plot(gmG8$g, main = "True DAG")
+ ## plot(dagitty:::graphLayout(dagitty_dag1))
+ 
+ res[1] <- (dagitty_dag1 == "dag {\nAuthor\nBar\nCtrl\nGoal\nV5\nV6\nV7\nV8\nAuthor -> Bar\nAuthor -> V6\nAuthor -> V8\nBar -> Ctrl\nBar -> V5\nV5 -> V6\nV5 -> V8\nV6 -> V7\n}\n")
+ 
+ #############
+ ## Test DAG 2
+ #############
+ set.seed(123)
+ p <- 10
+ V <- sample(LETTERS, p)
+ g <- pcalg::randomDAG(p,prob=0.3, V = V)
+ 
+ amat <- wgtMatrix(g)
+ amat[amat != 0] <- 1
+ dagitty_dag2 <- pcalg2dagitty(amat,V,type="dag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow=c(1,2))
+ ## plot(g, main = "True DAG")
+ ## plot(dagitty:::graphLayout(dagitty_dag2))
+ 
+ res[2] <- (dagitty_dag2 == "dag {\nA\nH\nJ\nK\nQ\nT\nU\nW\nX\nZ\nA -> Q\nH -> A\nH -> K\nH -> Q\nH -> T\nH -> Z\nJ -> W\nT -> A\nT -> Q\nT -> X\nU -> Q\nU -> W\nU -> X\nW -> K\n}\n")
+ 
+ ###############
+ ## Test CPDAG 1
+ ###############
+ data(gmG)
+ n <- nrow(gmG8$ x)
+ V <- colnames(gmG8$ x) # labels aka node names
+ 
+ ## estimate CPDAG
+ pc.fit <- pc(suffStat = list(C = cor(gmG8$x), n = n),
+              indepTest = gaussCItest, ## indep.test: partial correlations
+              alpha=0.01, labels = V, verbose = FALSE)
+ amat <- as(pc.fit, "amat")
+ dagitty_cpdag1 <- pcalg2dagitty(amat,V,type="cpdag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow = c(1,2))
+ ## plot(pc.fit)
+ ## plot(dagitty:::graphLayout(dagitty_cpdag1))
+ 
+ res[3] <- (dagitty_cpdag1 == "pdag {\nAuthor\nBar\nCtrl\nGoal\nV5\nV6\nV7\nV8\nAuthor -- Bar\nAuthor -> V6\nAuthor -> V8\nBar -- Ctrl\nBar -> V5\nV5 -> V6\nV5 -> V8\nV6 -> V7\n}\n")
+ 
+ stopifnot(all(res[1:3]))
+ 
+ if (doExtras) {
+ #############
+ ## Test CPDAG 2
+ #############
+ set.seed(135)
+ p <- 10
+ V <- sample(LETTERS, p)
+ g <- dag2cpdag(pcalg::randomDAG(p,prob=0.3, V = V))
+ 
+ amat <- wgtMatrix(g)
+ amat[amat != 0] <- 1
+ dagitty_cpdag2 <- pcalg2dagitty(amat,V,type="cpdag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow=c(1,2))
+ ## plot(g)
+ ## plot(dagitty:::graphLayout(dagitty_cpdag2))
+ 
+ res[4] <- (dagitty_cpdag2 == "pdag {\nA\nB\nH\nI\nJ\nK\nO\nS\nV\nX\nA -- I\nA -- J\nA -- V\nA -> B\nA -> O\nH -- I\nH -> B\nI -> B\nJ -- K\nK -> B\nS -- X\nS -> O\nV -> B\n}\n")
+ 
+ #############
+ ## Test MAG 1
+ #############
+ amat <- matrix(c(0,2,0,0, 2,0,3,3, 0,2,0,3, 0,2,2,0), 4,4)
+ V <- LETTERS[1:4]
+ colnames(amat) <- rownames(amat) <- V
+ ## plotAG(amat)
+ dagitty_mag1 <- pcalg2dagitty(amat,V,type="mag")
+ res[5] <- (dagitty_mag1 == "mag {\nA\nB\nC\nD\nA <-> B\nB -> C\nB -> D\nC -> D\n}\n")
+ 
+ #############
+ ## Test MAG 2
+ #############
+ set.seed(78)
+ p <- 8
+ g <- pcalg::randomDAG(p, prob = 0.4)
+ ## Compute the true covariance and then correlation matrix of g:
+ true.corr <- cov2cor(trueCov(g))
+ 
+ ## define nodes 2 and 6 to be latent variables
+ L <- c(2,6)
+ 
+ ## Find PAG
+ ## As dependence "oracle", we use the true correlation matrix in
+ ## gaussCItest() with a large "virtual sample size" and a large alpha:
+ true.pag <- dag2pag(suffStat = list(C= true.corr, n= 10^9),
+                     indepTest= gaussCItest, graph=g, L=L, alpha= 0.9999)
+ 
+ ## find a valid MAG such that no additional edges are directed into
+ (amat <- pag2magAM(true.pag@amat, 4)) # -> the adj.matrix of the MAG
+ ## plotAG(amat)
+ V <- colnames(amat)
+ dagitty_mag2 <- pcalg2dagitty(amat,V,type="mag")
+ res[6] <- (dagitty_mag2 == "mag {\n1\n2\n3\n4\n5\n6\n1 -> 4\n1 -> 5\n1 -> 6\n2 -> 5\n3 -> 4\n3 -> 6\n4 -> 5\n4 -> 6\n5 <-> 6\n}\n")
+ 
+ #############
+ ## Test PAG 1
+ #############
+ mFig4b <- matrix(c(0,0,1,0,0,0, 0,0,1,0,0,0, 2,2,0,0,3,2,
+                    0,0,0,0,2,2, 0,0,2,3,0,2, 0,0,2,3,2,0), 6,6)
+ V <- c("V1", "V2", "X", "Y", "V4", "V3")
+ colnames(mFig4b) <- rownames(mFig4b) <- V
+ ## plotAG(mFig4b)
+ 
+ dagitty_pag1 <- pcalg2dagitty(mFig4b,V,type="pag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow=c(1,2))
+ ## plot(g)
+ ## plot(dagitty:::graphLayout(dagitty_cpdag2))
+ 
+ res[7] <- (dagitty_pag1 == "pag {\nV1\nV2\nV3\nV4\nX\nY\nV1 @-> X\nV2 @-> X\nV3 -> Y\nV3 <-> V4\nV3 <-> X\nV4 -> Y\nX -> V4\n}\n")
+ 
+ #############
+ ## Test PAG 2
+ #############
+ set.seed(42)
+ p <- 7
+ ## generate and draw random DAG :
+ myDAG <- pcalg::randomDAG(p, prob = 0.4)
+ 
+ ## find skeleton and PAG using the FCI algorithm
+ suffStat <- list(C = cov2cor(trueCov(myDAG)), n = 10^9)
+ fm <- fci(suffStat, indepTest=gaussCItest,
+            alpha = 0.9999, p=p, doPdsep = FALSE)
+ 
+ amat <- as(fm, "amat")
+ V <- colnames(amat)
+ dagitty_pag2 <- pcalg2dagitty(amat,V,type="pag")
+ 
+ res[8] <- (dagitty_pag2 == "pag {\n1\n2\n3\n4\n5\n6\n7\n1 -> 7\n1 @-> 5\n1 @-> 6\n1 @-@ 3\n2 -> 7\n2 @-> 5\n2 @-> 6\n3 -> 7\n3 @-> 5\n3 @-> 6\n3 @-@ 4\n4 @-> 6\n5 @-> 7\n6 -> 7\n}\n")
+ 
+ #################
+ ## Test empty DAG
+ #################
+ set.seed(123)
+ p <- 10
+ V <- sample(LETTERS, p)
+ g <- pcalg::randomDAG(p,prob=0, V = V)
+ 
+ amat <- wgtMatrix(g)
+ amat[amat != 0] <- 1
+ dagitty_dagE <- pcalg2dagitty(amat,V,type="dag")
+ ## Use dagitty:::graphLayout instead of just graphLayout
+ ## because Rgraphviz package that R uses has a function w the same name
+ ## par(mfrow=c(1,2))
+ ## plot(g, main = "True DAG")
+ ## plot(dagitty:::graphLayout(dagitty_dagE))
+ 
+ res[9] <- (dagitty_dagE == "dag {\nA\nH\nJ\nK\nQ\nT\nU\nW\nX\nZ\n\n}\n")
+ 
+ #################
+ ## Test empty PAG
+ #################
+ set.seed(42)
+ p <- 7
+ ## generate and draw random DAG :
+ myDAG <- pcalg::randomDAG(p, prob = 0)
+ 
+ ## find skeleton and PAG using the FCI algorithm
+ suffStat <- list(C = cov2cor(trueCov(myDAG)), n = 10^9)
+ fm <- fci(suffStat, indepTest=gaussCItest,
+            alpha = 0.9999, p=p, doPdsep = FALSE)
+ 
+ amat <- as(fm, "amat")
+ V <- colnames(amat)
+ dagitty_pagE <- pcalg2dagitty(amat,V,type="pag")
+ 
+ res[10] <- (dagitty_pagE == "pag {\n1\n2\n3\n4\n5\n6\n7\n\n}\n")
+ 
+ stopifnot(all(res))
+ 
+ ########################################################
+ ## Test via comparison of gac() and isAdjustmentSet() ##
+ ########################################################
+ gacVSdagitty <- function(amat, x, y ,z, V, type) {
+     ## x,y,z: col positions as used in GAC
+     ## Result: TRUE is result is equal
+     typeDG <- switch(type,
+                      dag = "dag",
+                      cpdag = "cpdag",
+                      mag = "mag",
+                      pag = "pag")
+     
+     dgRes <- pcalg2dagitty(amat, V, type = typeDG)
+     Exp <- V[x]; Out <- V[y]; Z <- V[z]
+     gacRes <- gac(amat,x,y, z, type)$gac 
+     dgRes <- dagitty::isAdjustmentSet(x = dgRes, Z = Z, exposure = Exp, outcome = Out)
+     (gacRes == dgRes)
+ }
+ 
+ ## CPDAG 1: Paper Fig 1
+ ## mFig1 <- matrix(c(0,1,1,0,0,0, 1,0,1,1,1,0, 0,0,0,0,0,1,
+ ##                   0,1,1,0,1,1, 0,1,0,1,0,1, 0,0,0,0,0,0), 6,6)
+ ## V <- as.character(1:nrow(mFig1))
+ ## colnames(mFig1) <- rownames(mFig1) <- V
+ 
+ ## typeGAC <- "cpdag"
+ ## x <- 3; y <- 6
+ ## z <- c(2,4); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- c(4,5); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- c(4,2,1); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- c(4,5,1); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- c(4,2,5); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- c(4,2,5,1); gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- 2; gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ ## z <- NULL; gacVSdagitty(amat = mFig1, x=x, y=y, z=z, V=V, type=typeGAC)
+ 
+ xx <- TRUE
+ ##################################################
+ ## DAG / CPDAG
+ ##################################################
+ ## CPDAG 1: Paper Fig 1
+ mFig1 <- matrix(c(0,1,1,0,0,0, 1,0,1,1,1,0, 0,0,0,0,0,1,
+                   0,1,1,0,1,1, 0,1,0,1,0,1, 0,0,0,0,0,0), 6,6)
+ type <- "cpdag"
+ x <- 3; y <- 6
+ 
+ V <- as.character(1:ncol(mFig1))
+ rownames(mFig1) <- colnames(mFig1) <- V
+ 
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(2,4), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(4,5), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(4,2,1), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(4,5,1), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(4,2,5), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig1,x,y, z=c(4,2,5,1), V=V, type)
+ xx <- xx & gacVSdagitty(mFig1,x,y, z= 2,    V=V, type)
+ xx <- xx & gacVSdagitty(mFig1,x,y, z= NULL, V=V, type)
+ 
+ ## CPDAG 2: Paper Fig 5a
+ mFig5a <- matrix(c(0,1,0,0,0, 1,0,1,0,0, 0,0,0,0,1, 0,0,1,0,0, 0,0,0,0,0), 5,5)
+ V <- as.character(1:ncol(mFig5a))
+ rownames(mFig5a) <- colnames(mFig5a) <- V
+ 
+ type <- "cpdag"
+ x <- c(1,5); y <- 4
+ xx <- xx &  gacVSdagitty(mFig5a, x,y, z=c(2,3), V=V, type)
+ xx <- xx & gacVSdagitty(mFig5a, x,y, z= 2,     V=V, type)
+ 
+ ## DAG 1 from Marloes' Talk
+ mMMd1 <- matrix(c(0,1,0,1,0,0, 0,0,1,0,1,0, 0,0,0,0,0,1,
+                   0,0,0,0,0,0, 0,0,0,0,0,0, 0,0,0,0,0,0),6,6)
+ V <- as.character(1:ncol(mMMd1))
+ rownames(mMMd1) <- colnames(mMMd1) <- V
+ 
+ type <- "dag"
+ x <- 1; y <- 3
+ xx <- xx &  gacVSdagitty(mMMd1, x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd1, x,y, z= 2, V=V, type)
+ xx <- xx &  gacVSdagitty(mMMd1, x,y, z= 4, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd1, x,y, z= 5, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd1, x,y, z= 6, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd1, x,y, z=c(4,5), V=V, type)
+ 
+ ## DAG 2 from Marloes' Talk
+ mMMd2 <- matrix(c(0,1,0,1,0,0, 0,0,0,0,0,0, 0,1,0,0,1,0,
+                   0,0,0,0,1,0, 0,0,0,0,0,1, 0,0,0,0,0,0), 6,6)
+ V <- as.character(1:ncol(mMMd2))
+ rownames(mMMd2) <- colnames(mMMd2) <- V
+ 
+ type <- "dag"
+ x <- 4; y <- 6
+ xx <- xx &  gacVSdagitty(mMMd2, x,y, z= 1, V=V, type)
+ xx <- xx &  gacVSdagitty(mMMd2, x,y, z= 3, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd2, x,y, z= 5, V=V, type)
+ xx <- xx & gacVSdagitty(mMMd2, x,y, z=c(1,5), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMd2, x,y, z=c(1,2), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMd2, x,y, z=c(1,3), V=V, type)
+ xx <- xx & gacVSdagitty(mMMd2, x,y, z= 2, V=V, type)
+ 
+ ##################################################
+ ## PAG
+ ##################################################
+ type <- "pag"
+ mFig3a <- matrix(c(0,1,0,0, 1,0,1,1, 0,1,0,1, 0,1,1,0), 4,4)
+ V <- as.character(1:ncol(mFig3a))
+ rownames(mFig3a) <- colnames(mFig3a) <- V
+ xx <- xx & gacVSdagitty(mFig3a, x=2,      y=4, z=NULL,   V=V, type)
+ 
+ mFig3b <- matrix(c(0,2,0,0, 3,0,3,3, 0,2,0,3, 0,2,2,0), 4,4)
+ V <- as.character(1:ncol(mFig3b))
+ rownames(mFig3b) <- colnames(mFig3b) <- V
+ xx <- xx & gacVSdagitty(mFig3b, x=2,      y=4, z=NULL,   V=V, type)
+ 
+ mFig3c <- matrix(c(0,3,0,0, 2,0,3,3, 0,2,0,3, 0,2,2,0), 4,4)
+ V <- as.character(1:ncol(mFig3c))
+ rownames(mFig3c) <- colnames(mFig3c) <- V
+ xx <- xx &  gacVSdagitty(mFig3c, x=2,      y=4, z=NULL,   V=V, type)
+ 
+ mFig4a <- matrix(c(0,0,1,0,0,0, 0,0,1,0,0,0, 2,2,0,3,3,2,
+                    0,0,2,0,2,2, 0,0,2,1,0,2, 0,0,1,3,3,0), 6,6)
+ V <- as.character(1:ncol(mFig4a))
+ rownames(mFig4a) <- colnames(mFig4a) <- V
+ xx <- xx & gacVSdagitty(mFig4a, x=3,      y=4, z=NULL,   V=V, type)
+ xx <- xx &  gacVSdagitty(mFig4a, x=3,      y=4, z= 6,     V=V, type)
+ xx <- xx &  gacVSdagitty(mFig4a, x=3,      y=4, z=c(1,6), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig4a, x=3,      y=4, z=c(2,6), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig4a, x=3,      y=4, z=c(1,2,6), V=V, type)
+ 
+ mFig4b <- matrix(c(0,0,1,0,0,0, 0,0,1,0,0,0, 2,2,0,0,3,2,
+                    0,0,0,0,2,2, 0,0,2,3,0,2, 0,0,2,3,2,0), 6,6)
+ V <- as.character(1:ncol(mFig4b))
+ rownames(mFig4b) <- colnames(mFig4b) <- V
+ xx <- xx & gacVSdagitty(mFig4b, x=3,      y=4, z=NULL,   V=V, type)
+ xx <- xx & gacVSdagitty(mFig4b, x=3,      y=4, z= 6,     V=V, type)
+ xx <- xx & gacVSdagitty(mFig4b, x=3,      y=4, z=c(5,6), V=V, type)
+ 
+ mFig5b <- matrix(c(0,1,0,0,0,0,0, 2,0,2,3,0,3,0, 0,1,0,0,0,0,0, 0,2,0,0,3,0,0,
+                    0,0,0,2,0,2,3, 0,2,0,0,2,0,0, 0,0,0,0,2,0,0), 7,7)
+ V <- as.character(1:ncol(mFig5b))
+ rownames(mFig5b) <- colnames(mFig5b) <- V
+ xx <- xx & gacVSdagitty(mFig5b, x=c(2,7), y=6, z=NULL,   V=V, type)
+ xx <- xx &  gacVSdagitty(mFig5b, x=c(2,7), y=6, z=c(4,5), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig5b, x=c(2,7), y=6, z=c(4,5,1), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig5b, x=c(2,7), y=6, z=c(4,5,3), V=V, type)
+ xx <- xx &  gacVSdagitty(mFig5b, x=c(2,7), y=6, z=c(1,3,4,5), V=V, type)
+ 
+ ## PAG in Marloes' talk
+ mMMp <- matrix(c(0,0,0,3,2,0,0, 0,0,0,0,1,0,0, 0,0,0,0,1,0,0, 2,0,0,0,0,3,2,
+                  3,2,2,0,0,0,3, 0,0,0,2,0,0,0, 0,0,0,2,2,0,0), 7,7)
+ V <- as.character(1:ncol(mMMp))
+ rownames(mMMp) <- colnames(mMMp) <- V
+ 
+ x <- c(5,6); y <- 7
+ xx <- xx & gacVSdagitty(mMMp, x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(mMMp, x,y, z= 1,   V=V, type)
+ xx <- xx & gacVSdagitty(mMMp, x,y, z= 4,   V=V, type)
+ xx <- xx & gacVSdagitty(mMMp, x,y, z= 2,   V=V, type)
+ xx <- xx & gacVSdagitty(mMMp, x,y, z= 3,   V=V, type)
+ xx <- xx & gacVSdagitty(mMMp, x,y, z=c(2,3), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMp, x,y, z=c(1,4), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMp, x,y, z=c(1,4,2), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMp, x,y, z=c(1,4,3), V=V, type)
+ xx <- xx &  gacVSdagitty(mMMp, x,y, z=c(1,4,2,3), V=V, type)
+ 
+ ##################################################
+ ## V=V, type = "pag" -- Tests from Ema
+ ##################################################
+ type <- "pag"
+ pag.m <- readRDS(system.file("external/gac-pags.rds", package="pcalg"))
+ m1 <- pag.m[["m1"]]
+ V <- colnames(m1)
+ x <- 6; y <- 9
+ xx <- xx & gacVSdagitty(m1,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=1, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=3, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=4, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,7,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,5,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,5,7,8), V=V, type)
+ 
+ x <- c(6,8); y <- 9
+ xx <- xx & gacVSdagitty(m1,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=1, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=3, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=4, V=V, type)
+ xx <- xx &  gacVSdagitty(m1,x,y, z=c(2,3), V=V, type)
+ xx <- xx &  gacVSdagitty(m1,x,y, z=c(2,3,4), V=V, type)
+ xx <- xx &  gacVSdagitty(m1,x,y, z=c(2,3,7), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,5), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,3,5,7), V=V, type)
+ 
+ x <- 3; y <- 1
+ xx <- xx & gacVSdagitty(m1,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=4, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=5, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=6, V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,6), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,7,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,5,8), V=V, type)
+ xx <- xx & gacVSdagitty(m1,x,y, z=c(2,5,7,8), V=V, type)
+ 
+ m2 <- pag.m[["m2"]]
+ V <- colnames(m2)
+ x <- 3; y <-1
+ xx <- xx & gacVSdagitty(m2,x,y, z=NULL, V=V, type)
+ xx <- xx &  gacVSdagitty(m2,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=4, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=c(2,8), V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=8, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=9, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=c(2,8,9), V=V, type)
+ xx <- xx &  gacVSdagitty(m2,x,y, z=c(2,5), V=V, type)
+ 
+ x <- c(3,9); y <- 1
+ xx <- xx & gacVSdagitty(m2,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=4, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=c(2,8), V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=8, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=9, V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=c(2,8,9), V=V, type)
+ xx <- xx & gacVSdagitty(m2,x,y, z=c(2,5), V=V, type)
+ 
+ m3 <- pag.m[["m3"]]
+ V <- colnames(m3)
+ x <- 1; y <- 9
+ xx <- xx & gacVSdagitty(m3,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=3, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=5, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=7, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=8, V=V, type)
+ xx <- xx &  gacVSdagitty(m3,x,y, z=c(2,3), V=V, type)
+ xx <- xx &  gacVSdagitty(m3,x,y, z=c(5,7), V=V, type)
+ 
+ x <- 1; y <- 8
+ xx <- xx & gacVSdagitty(m3,x,y, z=NULL, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=2, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=3, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=5, V=V, type)
+ xx <- xx &  gacVSdagitty(m3,x,y, z=7, V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=9, V=V, type)
+ xx <- xx &  gacVSdagitty(m3,x,y, z=c(2,3), V=V, type)
+ xx <- xx & gacVSdagitty(m3,x,y, z=c(5,9), V=V, type)
+ 
+ if (!xx) {
+     stop("Problem when testing function gacVSdagitty.")
+ } else {
+     message("OK, no issues were found.")
+ }
+ }
+ }
Loading required namespace: dagitty

Attaching package: 'dagitty'

The following object is masked from 'package:pcalg':

    randomDAG

> 
> proc.time()
   user  system elapsed 
   1.56    0.18    1.68