  Although power laws of the Zipf type have been used by many workers to fit
rank distributions in different fields like in economy, geophysics, genetics,
soft-matter, networks etc., these fits usually fail at the tails. Some
distributions have been proposed to solve the problem, but unfortunately they
do not fit at the same time both ending tails. We show that many different data
in rank laws, like in granular materials, codons, author impact in scientific
journal, etc. are very well fitted by a beta-like function. Then we propose
that such universality is due to the fact that a system made from many
subsystems or choices, imply stretched exponential frequency-rank functions
which qualitatively and quantitatively can be fitted with the proposed
beta-like function distribution in the limit of many random variables. We prove
this by transforming the problem into an algebraic one: finding the rank of
successive products of a given set of numbers.
