Acronyms are CANCELLED

https://academia.stackexchange.com/questions/160171/its-2020-can-i-should-i-change-the-name-of-this-distribution

Starting from 2021, researchers are going to be called out not only for using politically-incorrect phrases, but also for using any word with Levenshtein distance of 3 or less from any of the forbidden words.

Imagine being a reneissance mathematician coming up with a theorem that’s cancelled in 2020 because it of the name.

checks wikipedia

The normal-inverse Gaussian distribution can also be seen as the marginal distribution of the normal-inverse Gaussian process which provides an alternative way of explicitly constructing it. Starting with a drifting Brownian motion (Wiener process), W ( γ ) ( t ) = W ( t ) + γ t {\displaystyle W^{(\gamma )}(t)=W(t)+\gamma t} W^{(\gamma )}(t)=W(t)+\gamma t, we can define the inverse Gaussian process A t = inf { s > 0 : W ( γ ) ( s ) = δ t } . {\displaystyle A_{t}=\inf{s>0:W^{(\gamma )}(s)=\delta t}.} A_{t}=\inf{s>0:W^{(\gamma )}(s)=\delta t}. Then given a second independent drifting Brownian motion, W ( β ) ( t ) = W ~ ( t ) + β t {\displaystyle W^{(\beta )}(t)={\tilde {W}}(t)+\beta t} W^{(\beta )}(t)={\tilde {W}}(t)+\beta t, the normal-inverse Gaussian process is the time-changed process X t = W ( β ) ( A t ) {\displaystyle X_{t}=W^{(\beta )}(A_{t})} X_{t}=W^{(\beta )}(A_{t}). The process X ( t ) {\displaystyle X(t)} X(t) at time t = 1 {\displaystyle t=1} t=1 has the normal-inverse Gaussian distribution described above. The NIG process is a particular instance of the more general class of Lévy processes.

it's 2020

AKA

MUH CURRENT YEAR

LOL, retard detected (the question's author)!

What if I were to model a class that converts data, in some form, such that the output conforms to this distribution? How would I name such a class?

>>5
The African Converter class.