library(RSiena) ##test3 mynet1 <- sienaDependent(array(c(tmp3, tmp4),dim=c(32, 32, 2))) mydata <- sienaDataCreate(mynet1) myeff<- getEffects(mydata) mymodel<- model.create(findiff=TRUE, fn = simstats0c, cond=FALSE, nsub=2, n3=50, seed=3) print('test3') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) #,dll='../siena/src/RSiena.dll') ans (myeff <- includeEffects(myeff, transTrip, cycle4)) (myeff <- includeEffects(myeff, cycle4, include=FALSE)) ##test4 mymodel$cconditional <- TRUE mymodel$condvarno<- 1 print('test4') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll') ans ##test5 mynet1 <- sienaDependent(array(c(tmp3,tmp4),dim=c(32,32,2))) mydata <- sienaDataCreate(mynet1) myeff<- getEffects(mydata) mymodel<- model.create(fn = simstats0c, nsub=2, n3=50, cond=FALSE, seed=5) print('test5') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ans (myeff <- includeEffects(myeff, recip, inPop)) (myeff <- includeEffects(myeff, outAct, fix=TRUE, test=TRUE)) (myeff <- includeInteraction(myeff, recip, inPop, fix=TRUE, test=TRUE)) ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ans score.Test(ans) ##test6 mynet1 <- sienaDependent(array(c(tmp3,tmp4),dim=c(32,32,2))) mydata <- sienaDataCreate(mynet1) myeff<- getEffects(mydata) mymodel<- model.create(fn = simstats0c, nsub=2, n3=50, cond=FALSE, doubleAveraging=0,seed=5) print('test6') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ans myeff <- includeEffects(myeff, recip, include=FALSE) myeff <- includeEffects(myeff, recip, type='endow') myeff <- includeEffects(myeff, recip, type='creation') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ans testSame.RSiena(ans, 3, 4) ##test7 mynet1 <- sienaDependent(array(c(tmp3,tmp4),dim=c(32,32,2))) mydata <- sienaDataCreate(mynet1) myeff<- getEffects(mydata) mymodel<- model.create(fn = simstats0c, nsub=2, n3=50, cond=FALSE, diagonalize=0.5, seed=5) print('test7') ans<- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll') ans ##test8 mymodel<- model.create(fn = simstats0c, nsub=1, n3=50, cond=TRUE, condvarno=1, seed=5) print('test8') ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll') ans ##test9 mynet1 <- sienaDependent(array(c(s501, s502, s503), dim=c(50, 50, 3))) mynet2 <- sienaDependent(s50a,type='behavior') mydata <- sienaDataCreate(mynet1, mynet2) myeff <- getEffects(mydata) myeff <- setEffect(myeff, linear, initialValue=0.34699930338, name="mynet2") myeff <- setEffect(myeff, avAlt, name="mynet2", interaction1="mynet1") ##myeff$initialValue[98] <- 0.34699930338 ## siena3 starting values differ ##test10 print('test10') mymodel$cconditional <- TRUE mymodel$condvarno<- 1 ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE) ##, verbose=TRUE) ans ##test11 print('test11') mymodel<- model.create(fn = simstats0c, nsub=1, n3=50, behModelType=c(mynet2=2), seed=6) (ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE)) ##test12 print('test12') use<- 1:30 mynet1 <- sienaDependent(array(c(s501[use,], s502[use,], s503[use,]), dim=c(length(use), 50,3)), type='bipartite', nodeSet=c('Senders','receivers')) receivers <- sienaNodeSet(50,'receivers') senders <- sienaNodeSet(30,'Senders') myvar1 <- coCovar(s50a[1:30,2], nodeSet='Senders') mydata <- sienaDataCreate(mynet1, myvar1, nodeSets=list(senders, receivers)) myeff <- getEffects(mydata) myeff <- includeEffects(myeff, inPop) myeff <- setEffect(myeff, altInDist2, interaction1="myvar1", parameter=1) ans <- siena07(sienaModelCreate(n3=50, nsub=2, seed=1), data=mydata, effects=myeff, batch=TRUE, silent=TRUE) ans tt <- sienaTimeTest(ans) summary(tt) ##test13 print('test13') use<- 1:30 mynet1 <- sienaDependent(array(c(s502[,use], s503[,use]), dim=c(50, length(use), 2)), type='bipartite', nodeSet=c('Senders','receivers')) receivers <- sienaNodeSet(30,'receivers') senders <- sienaNodeSet(50,'Senders') myvar1 <- coCovar(s50a[1:50,2], nodeSet='Senders') mydata <- sienaDataCreate(mynet1, myvar1, nodeSets=list(senders, receivers)) myeff <- getEffects(mydata) myeff <- setEffect(myeff, altInDist2, interaction1="myvar1", parameter=1) myeff <- setEffect(myeff, egoX, interaction1="myvar1") (ans <- siena07(sienaModelCreate(n3=50, nsub=2, seed=1), data=mydata, effects=myeff, batch=TRUE, silent=TRUE)) ##test14 print('test14') net <- sienaDependent(array(c(tmp3, tmp4), dim=c(32, 32, 2))) dataset <- sienaDataCreate(net) myeff <- getEffects(dataset) myeff <- includeEffects(myeff, inPop) algo <- sienaAlgorithmCreate(nsub=1, n3=20, maxlike=TRUE, seed=15, mult=1, prML=1) (ans <- siena07(algo, data=dataset, effects=myeff, batch=TRUE, silent=TRUE)) algo <- sienaAlgorithmCreate(nsub=1, n3=20, maxlike=TRUE, seed=15, mult=1, prML=2) (ans <- siena07(algo, data=dataset, effects=myeff, batch=TRUE, silent=TRUE)) ##test 15 print('test15') mynet1 <- sienaDependent(array(c(s501, s502, s503), dim=c(50, 50, 3))) mynet2 <- sienaDependent(s50a,type='behavior') mydata <- sienaDataCreate(mynet1, mynet2) myeff <- getEffects(mydata) (myeff <- includeEffects(myeff, transTrip)) (myeff <- includeEffects(myeff, egoX, simX, interaction1="mynet2")) (myeff <- includeEffects(myeff, avSim, name="mynet2", interaction1="mynet1")) (myeff <- includeGMoMStatistics(myeff, simX_gmm, interaction1="mynet2")) algo <- sienaAlgorithmCreate(nsub=1, n3=100, gmm=TRUE, seed=6) (ans <- siena07(algo, data=mydata, effects=myeff, batch=TRUE, parallelTesting=TRUE, silent=TRUE)) ##test16 print('test16') set.seed(123) # simulate behavior data according to dZ(t) = [-0.1 Z + 1] dt + 1 dW(t) y1 <- rnorm(50, 0,3) y2 <- exp(-0.1) * y1 + (1-exp(-0.1)) * 1/ -0.1 + rnorm(50, 0, (exp(-0.2)- 1) / -0.2 * 1^2) friend <- sienaDependent(array(c(s501, s502), dim = c(50,50,2))) behavior <- sienaDependent(matrix(c(y1,y2), 50,2), type = "continuous") (mydata <- sienaDataCreate(friend, behavior)) (myeff <- getEffects(mydata, onePeriodSde = TRUE)) algorithmMoM <- sienaAlgorithmCreate(nsub=1, n3=20, seed=321) (ans <- siena07(algorithmMoM, data = mydata, effects = myeff, batch=TRUE)) ##test17 print('test17') mynet <- sienaNet(array(c(s501, s502), dim=c(50, 50, 2))) sm1 <- 1*(s50s[,2] >= 2) sm2 <- 1*(s50s[,3] >= 2) sm2 <- pmax(sm1,sm2) sm2[c(33,28,29,44)] <- 1 mybeh <- sienaDependent(cbind(sm1,sm2), type="behavior") (mydata <- sienaDataCreate(mynet, mybeh)) mymodel <- sienaModelCreate(projname=NULL, seed=1234, firstg=0.001, nsub=1, n3=10) myeff <- getEffects(mydata) (myeff <- setEffect(myeff,avExposure,type='rate',parameter=2, name='mybeh',interaction1='mynet')) (ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE)) ##test18 print('test18') myalgorithm <- sienaAlgorithmCreate(nsub=1, n3=10, seed=1293) mynet1 <- sienaDependent(array(c(tmp3, tmp4), dim=c(32, 32, 2))) cova <- coCovar(1:32) cova2 <- coCovar(rep(0,32), warn=FALSE) mydata <- sienaDataCreate(mynet1, cova) mydata2 <- sienaDataCreate(mynet1, cova=cova2) mygroup <- sienaGroupCreate(list(mydata,mydata2)) myeff <- getEffects(mygroup) myeff <- setEffect(myeff, simX, interaction1='cova') (ans <- siena07(myalgorithm, data=mygroup, effects=myeff, batch=TRUE)) ## delete output file if (file.exists('Siena.txt')){unlink('Siena.txt')}