uses or ways to understand the 5th order moment of a distribution?


Smelly poop man with doo doo pants.
hello forum,

as much as i'd like to believe it's not true, winter break is coming to an end which means i'm slowly getting back to my uni stuff. which means i need to start staring at my dissertation topic.

some random dude with some random article in my field (Fleishman, 1978 to be more precise) has influenced a lot the way in which we describe distributions by saying that as long as we have the first 4th order moments (mean, variance, skewness, kurtosis) we pretty much can describe the stuff we need from a distribution.

i am in need to wrap my head around the 5th order moment and so far the only intuitive thing i find is that it helps "describe" the behaviour of the distribution in its tails.

does anyone understand why? or maybe some useful reference?