bclust (version 1.2)

imp: calculates variable and variable-cluster importances

Description

The function computes the log Bayes factors for the hypothesis H0: the variable or the variable-cluster combination is useful for clustering against H1: the variable or the variable-cluster combination is useless. The Bayes factors are computed for the optimal allocation found by the bclust function.

Usage

imp(x)

Arguments

x

A bclustvs object.

Value

• var
  A vector being the log Bayes factor of $\delta_v=1$ against $\delta_v=0$, see bclust for details.
• varclust
  A vector being the log Bayes factor of $\gamma_{vc}=1$ against $\gamma_{vc}=0$, see bclust for details.
• repno
  The number of replicates producing each row of varclust.
• labels
  The vector of variable labels extracted from the bclustvs object.
• order
  The order of var useful to sort var, varclust, and labels.

See Also

bclust.

Examples

data(gaelle)

gaelle.id<-rep(1:14,c(3,rep(4,13))) 
# first 3 rows replication of ColWT, 4 for the rest

gaelle.bclust<-bclust(gaelle,rep.id=gaelle.id,
transformed.par=c(-1.84,-0.99,1.63,0.08,-0.16,-1.68),
var.select=TRUE)

gaelle.imp<-imp(gaelle.bclust)

#plot the variable importances 
par(mfrow=c(1,1)) #retreive graphic defaults 

mycolor<-gaelle.imp$var
mycolor<-c()
mycolor[gaelle.imp$var>0]<-"black"
mycolor[gaelle.imp$var<=0]<-"white"

viplot(var=gaelle.imp$var,xlab=gaelle.imp$labels,col=mycolor)
#plot important variables with balck

viplot(var=gaelle.imp$var,xlab=gaelle.imp$labels,
sort=TRUE,col=heat.colors(length(gaelle.imp$var)),
xlab.mar=10,ylab.mar=4)
mtext(1, text = "Metabolite", line = 7,cex=1.5)# add x axis label
mtext(2, text = "Log Bayes Factor", line = 3,cex=1.2)# add y axis labels
#sort importnaces and use heat colors add some labels to the x and y axes