Hi. I have made 100 experiments of an M/M/1 queue, and for each one I have
calculated both, mean and variance of the queue size. Now, a professor has told
me that variance is usually chi-squared distributed. Is there a way in R that I
can find the parameter that best fits a chi-square to the variance data? I know
there's fitdistr()m but this function doesn't handle chi-square. I believe the
mean estimator for the chi-square is df (degrees of freedom). The theoretical
variance for an M/M/1 queue with lambda=30/33 is ~108. So, should I expect the
chi-square with parameter 108 is the one that best fits the data?
Thanks a lot for your help.
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