This article presents two methods to sample uniform subtrees from graphs using
Metropolis-Hastings algorithms. One method is an independent Metropolis-Hastings and
the other one is a type of add-and-delete MCMC.
In addition to the theoretical contributions, we present simulation studies which con-
firm the theoretical convergence results on our methods by monitoring the convergence of
our Markov chains to the equilibrium distribution