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Hi Caroline, you wrote: > > In the model random numbers for the service procedure are generated > using > > the inverse transformation method, to create 'a day in the life' of the > lock > > system. I inititally modelled the lock procedure(service) using the > Normal > > distribution, as it fits this distribution. However on occasions, due > to > > high variance, there is a small chance that negative values can be > produced. > > This is clearly not acceptable as it cannot take minus 0.5 minutes for a > > boat to enter a lock. In view of constraint I have now chosen > Log-Normal > > because it is closely related to the Normal distribution, but is also is > a > > positive and positively skewed distribution. > > > > Has anyone else used a Log-Normal distribution to describe length of > service > > in a simulation model. Can anyone offer more information on this > > distribution as there appears to be very little written about it, > compared > > to the Normal. > Although based on the normal the lognormal is signifiicantly skewed, which may on may not be a feature of the problem. If you want a distribution which is also is likely to mimic the normal then, apart from the truncation method which Mike suggests (and which actually then underestimates the variance), why not use a Gamma distribution? Gamma distributions can approximate normal distributions when the shape parameter is high, and they are always non-negative. If the likelIhood of the value being truncated is small (mean > 2-3 standard deviations from zero) then they will be similar. >From what I know about canal boats (having holidayed on them for several years) there is in fact likely to be a significant minimum value for time for a boat to enter a lock - ever if it was nosed up to the lock gates to start with, if you use any of the distributions as given then you will generate impossibly small values unless you allow for this. Similar physical considerations also apply to time ot fill/emplty the lock and for a boat ot exit. You probably need a model: time to enter: = constant + postive skewed distribution where the distribution might well be a Gamma or Log-normal. If you have some actual data (even mean and standard deviation) then once you can come up with a minimum figure which should be subtracted from the mean you can then estimate the parameters of your distribution. regards, -- Toni Roome Senior Lecturer in Statistics and OR Pathway leader MSc. Decision Sciences "One should each day, try to hear a little song, read a good poem, see a fine picture, and, if it is possible, speak a few reasonable words" (Goethe) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%