require(semtree) data(lgcm) lgcm$agegroup <- ordered(lgcm$agegroup, labels=c("young","old") ) lgcm$training <- as.factor(lgcm$training) lgcm$noise <- as.factor(lgcm$noise) # LOAD IN OPENMX MODEL. # A SIMPLE LINEAR GROWTH MODEL WITH 5 TIME POINTS FROM SIMULATED DATA manifests <- names(lgcm)[1:5] lgcModel <- mxModel("Linear Growth Curve Model Path Specification", type="RAM", manifestVars=manifests, latentVars=c("intercept","slope"), # residual variances mxPath( from=manifests, arrows=2, free=TRUE, values = c(1, 1, 1, 1, 1), labels=c("residual1","residual2","residual3","residual4","residual5") ), # latent variances and covariance mxPath( from=c("intercept","slope"), connect="unique.pairs", arrows=2, free=TRUE, values=c(1, 1, 1), labels=c("vari", "cov", "vars") ), # intercept loadings mxPath( from="intercept", to=manifests, arrows=1, free=FALSE, values=c(1, 1, 1, 1, 1) ), # slope loadings mxPath( from="slope", to=manifests, arrows=1, free=FALSE, values=c(0, 1, 2, 3, 4) ), # manifest means mxPath( from="one", to=manifests, arrows=1, free=FALSE, values=c(0, 0, 0, 0, 0) ), # latent means mxPath( from="one", to=c("intercept", "slope"), arrows=1, free=TRUE, values=c(1, 1), labels=c("meani", "means") ), mxData(lgcm,type="raw") ) # TREE CONTROL OPTIONS. # TO OBTAIN BASIC/DEFAULT SMETREE OPTIONS, SIMPLY TPYE THE FOLLOWING: controlOptions <- semtree.control(method = "naive",max.depth = 0,min.N=NULL, min.bucket=NULL) # RUN TREE. tree <- semtree(model=lgcModel, data=lgcm, control = controlOptions) stopifnot(tree$control$min.N==50) stopifnot(tree$control$min.bucket==25) x<-semtree_control() semtree:::check.semtree.control(x) x<-semtree_control(min.N=100) semtree:::check.semtree.control(x) x<-semtree_control(min.N=100, min.bucket=10) semtree:::check.semtree.control(x)