Hi there,(adsbygoogle = window.adsbygoogle || []).push({});

I'm working on a simulation of the travel patterns of cars. There are many variables and conditional probabilities in the model.

My question is, is there anything wrong with fitting all non parametric distributions to variables (both continuous and discrete)? The software I'm using fits lots (50+) different parametric distributions to data and ranks them in order of best fit. Some are very good fits but some are not very good fits. But I can't check every single distribution in a simulation, so would it be reasonable to fit all non parametric distributions?

I believe it is called fitting an Ogive distribution http://www.vosesoftware.com/ModelRi...ntinuous_distributions/Ogive_distribution.htm

Thanks

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# Parametric versus no parametric distributions

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