##longRPart 2 library(longRPart) 3 4 data(pbkphData) 5 pbkphData$Time=as.factor(pbkphData$Time) 6 long.tree = 7 longRPart(pbkph~Time,~age+gender,~1|Subject,pbkphData,R=corExp(form=~time)) 8 lrpTreePlot(long.tree, use.n=TRE, place="bottomright") REEMtree This package is useful for longitudinal studies where random effects exist. This example uses the dataset available in the package. pbkphData longRPart ################## ## REEMtree Random Effects for Longitudinal Data 1 library(REEMtree) 2 pbkphData.sub = subset(pbkphData, 3 !is.na(pbkphData$pbkph)) 4 reem.tree = data=pbkphData.sub, 5 random=~1|Subject) 6 plot(reem.tree) 7 ranef(reem.tree) #random effects 8 9 reem.tree = REEMtree(pbkph~Time, data=pbkphData.sub, 10 random=~1|Subject, 11 correlation=corAR1()) plot(reem.tree) 1 Related In "R bloggers" In "R bloggers" by Joseph Rickert The rxDTree() function included in the RevoScaleR package distributed with Revolution R Enterprise is an an example of a new class of algorithms that are being developed to deal with very large data sets. Although the particulars differ, what these algorithms have in common is the use… In "R bloggers"
2 3 4 5 6 7 8 ##longRPart library(longRPart) data(pbkphData) pbkphData$Time=as.factor(pbkphData$Time) long.tree = longRPart(pbkph~Time,~age+gender,~1|Subject,pbkphData,R=corExp(form=~time)) lrpTreePlot(long.tree, use.n=TRE, place="bottomright") REEMtree This package is useful for longitudinal studies where random effects exist. This example uses the pbkphData dataset available in the longRPart package. 1 2 3 4 5 6 7 8 9 10 11 ################## ## REEMtree Random Effects for Longitudinal Data library(REEMtree) pbkphData.sub = subset(pbkphData, !is.na(pbkphData$pbkph)) reem.tree = data=pbkphData.sub, random=~1|Subject) plot(reem.tree) ranef(reem.tree) #random effects reem.tree = REEMtree(pbkph~Time, data=pbkphData.sub, random=~1|Subject, correlation=corAR1()) plot(reem.tree) 1 Related In "R bloggers" In "R bloggers" by Joseph Rickert The rxDTree() function included in the RevoScaleR package distributed with Revolution R Enterprise is an an example of a new class of algorithms that are being developed to deal with very large data sets. Although the particulars differ, what these algorithms have in common is the use… In "R bloggers"
a_brief_tour_of_the_trees_and_forests.docx