# \donttest{
set.seed(1000)
junk<-rweibull(300,3,2)
## Fitting mixture of generalised lambda distributions on the data set using
## both the maximum likelihood and partition maximum likelihood and plot the
## resulting fits
junk<-fun.auto.bimodal.ml(faithful[,1],per.of.mix=0.1,clustering.m=clara,
init1.sel="rprs",init2.sel="rmfmkl",init1=c(-1.5,1.5),init2=c(-0.25,1.5),
leap1=3,leap2=3)
fun.plot.fit.bm(nclass=50,fit.obj=junk,data=faithful[,1],
name="Maximum likelihood using",xlab="faithful1",param.vec=c("rs","fmkl"))
## Do a quantile plot on the raw quantiles
qqplot.gld.bi(faithful[,1],junk$par,param1="rs",param2="fmkl",
name="RS FMKL ML fit")
## Or a qq plot to examine deviation from straight line
qqplot.gld.bi(faithful[,1],junk$par,param1="rs",param2="fmkl",
name="RS FMKL ML fit",type="str.qqplot")
# }
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