Update: I have recreated an artificial distribution using uniform random
numbers
n <- c(runif(Car[1],0,2), runif(Car[2],2,5),runif(Car[3],5,10),
runif(Car[4],10,20),
runif(Car[5],20,30), runif(Car[6],30,40), runif(Car[7],40,60),
runif(Car[8],60,200) )
The resulting density distribution is very jumpy, but should, in theory
allow me to fit a distribution to it and then extract the bin means from a
random sample of the given distribution. Again, this is tedious and far from
ideal, but cannot see any way around it. Also the distributions I fit to
this artificial dataset shoot up to infinity as x => 0.
Any ideas anyone???
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