[Solved] How should I choose a probability distribution to represent uncertainty?
Hi there, I am still learning Analytica and wondering which probability distribution I should pick for my model. Is there documentation on recommended distributions for different applications? Thanks for any help!
Take a look at Choosing a distribution page in the Analytica wiki. For most purposes if the quantity is continuous, with or without bounds, it’s convenient to use the built-in function UncertainLMH(xlow, xmedian, xhigh) distribution. You specify 10th, 50th, and 90th percentiles for xlow, xmedian, and xhigh parameters. You can also specify plow as, for example 20%, in which case xlow and xhigh are the 20th and 80th percentiles. You can also set lower and/or upper bounds as lb and ub. It uses a simple but effective algorithm (from Hadlock & Bickel, or Tom Keelin) to create a smooth distribution between the specified values. Hope this helps!  |
If you're talking about representing a subjective probability distribution, you probably can judge whether a crude first cut should be normal, lognormal, uniform, or triangular. That's a lot better than just assuming normal distributions. One good possibility is sometimes what Krista Myers suggested.
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