I have a small data set (n=25) with an unknown distribution and I'm trying to find a distribution function that is as similar as possible in order to ultimately determine tolerance limits. I used the EnvStat (eevd function) and tolerance (exttol.int function with the Gumbel specification) packages to adjust an extreme value distribution and got significantly different values for the parameters. I suspect the problem is with the tolerance package because when generating random numbers with these parameters there are significant deviations from the original data. My question is whether there actually are differences in the theoretical distribution functions underlying the packages - unfortunately my statistical skills are not sufficient to check this myself. My data: x <- c(51.86583, 59.39621, 90.06303, 57.75621, 37.50628, 67.91501, 51.62459, 59.98771, 55.37674, 14.71149, 49.16140, 69.00756, 59.44430, 60.32828, 40.66241, 90.62933, 50.55091, 52.42641, 61.48249, 68.93989, 51.45097, 31.96273, 74.08706, 37.44214, 56.29700)
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tolerance::exttol.intcall, if you useext="max"the methods seem to match. – PBulls Feb 12 '24 at 15:40