🚀 go-pugleaf

I would like to do similar analysis to a "best subset search" for regression
models (methods include regression by leaps and bounds, forward/backward
selection, all subsets, etc.) for which is "non-divisible".  By this I mean
that one can rank the values of the independent and/or dependent variables
from 1 to N, but a ranking of 2 is NOT TWICE BIG AS A ONE, etc.  Some of
the models I am looking at actually have mixtures of divisible and non-divisible
independent variables.  I am also looking at models in which the dependent
variable is either non-divisible or divisible.  I want to find something
analogous to regression for these kinds of models.  I am sure that any method
that can be dug up will be less powerful than regression.

Is there any method to handle such models?

Jeff Horn