visualiseGroupweights | R Documentation |
Plot group weights from multiple cross-validation folds.
visualiseGroupweights(dfGrps, Groupset, groupset.grouplvl, values, widthBoxplot = 0.05, boxplot = TRUE, jitter = TRUE, ps = 1.5, ls = 1)
dfGrps |
Data frame containing the following variables; 'Group': factor with group names; 'Group.weight': group weight of each group; 'Fold': number indicating which fold in the cross-validation is used. |
Groupset |
List of G elements containing covariate indices for each group |
groupset.grouplvl |
(optional): groups on group level, e.g. defining a hierarchical structure. |
values |
(optional): values of continuous co-data. If given, group weights are plotted against these value. |
widthBoxplot |
Width of boxplot. |
boxplot |
Should a boxplot be plotted? |
jitter |
Should point estimates be jittered? |
ps |
Point size. |
ls |
Line size. |
Plot in ggplot object.
visualiseGroupset
to visualise group sets and visualiseGroupsetweights
to plot estimated group set weights.
#discrete groups groupset1 <- list(1:20,21:40) dfGrps1 <- data.frame(Group=as.factor(rep(c(1,2),each=10)), Group.weight=c(rnorm(10,0.5,0.01),rnorm(10,2,0.05)), Fold=rep(1:10,2)) visualiseGroupweights(dfGrps1, Groupset=groupset1) #continous co-data groups cont.codata <- seq(0,1,length.out=40) #continuous co-data #only split at lower continous co-data group groupset2 <- splitMedian(values=cont.codata,split="lower",minGroupSize=10) #obtain groups on group level defining the hierarchy groupset.grouplvl <- obtainHierarchy(groupset2) #simulate random group weights around 1 dfGrps2 <- data.frame(Group=as.factor(rep(1:length(groupset2),each=10)), Group.weight=c(rnorm(10*length(groupset2),1,0.01)), Fold=rep(1:10,length(groupset2))) #plot group weights per group visualiseGroupweights(dfGrps2, Groupset=groupset2, groupset.grouplvl=groupset.grouplvl) #plot group weights per leaf group in the hierarchical tree visualiseGroupweights(dfGrps2, Groupset=groupset2, groupset.grouplvl=groupset.grouplvl, values=cont.codata)
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