Palisade Knowledge Base

HomeTechniques and Tips@RISK Distribution FittingBest Fit for Small Data Sets?

4.14. Best Fit for Small Data Sets?

Applies to: @RISK 6.x/7.x, Professional and Industrial Editions

When I do a fit on {1,2,3,4,5} as discrete data, @RISK prefers a RiskPoisson distribution, even though the RiskIntUniform is clearly a better fit. Why is that?

In @RISK 6.x, the default statistic for measuring goodness of fit is AIC (more specifically, AICc). For small data sets, the AIC calculation strongly prefers distributions with fewer parameters. (This is an application of the principle of parsimony.) The Poisson distribution and the geometric distribution (RiskGeomet) are both one-parameter distributions, but the uniform integer distribution (RiskIntUniform) is a two-parameter distribution. With a data set of only five points, the AIC statistic's preference for distributions with fewer parameters trumps the poorer likelihood functions computed for those distributions.

There are three countermeasures:

Last edited: 2015-06-19


This page was: Helpful | Not Helpful