  Kitamura and Stoye (2014) develop a nonparametric test for linear inequality
constraints, when these are are represented as vertices of a polyhedron instead
of its faces. They implement this test for an application to nonparametric
tests of Random Utility Models. As they note in their paper, testing such
models is computationally challenging. In this paper, we develop and implement
more efficient algorithms, based on column generation, to carry out the test.
These improved algorithms allow us to tackle larger datasets.
