I am interested in frequency distributions that are not normally distributed. If I have a frequency distributions table which is not normally distributed. Is there a function or package that will identify the type of distribution for me?
2 Answers
You can use the fitdistr
function (library MASS i think) and check for yourself if you find a 'fitting' distribution. However i suggest that you plot the function first and see how it looks like. This approach is generally not recommended as you always can use different parameters to fit a distribution and thus confuse one distribution with another. If you have found a suited distribution you should test it against data.
Edit: For instance a normal distribution may look like a poisson distribution. Fitting is in my oppinion only useful if you have enough random variables. Otherwise just draw variables from your data if you need to
You can always try to test whether a distribution is adequate for your data with QQ plot. If you have data that is dynamic, I would suggest that you use ECDF (Empirical Cumulative Distribution Function) which will give you more precise distributions as your data grows. You can use ECDF in R with the ecdf() function.

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