  This paper analyzes the performance of sequential importance sampling
algorithms for estimating the number of perfect matchings in bipartite graphs.
Precise bounds on the number of samples required to yield an accurate estimate
are derived. In doing so, moments of permutation statistics are computed using
generating functions and nonstandard limit theorems are derived by expressing
perfect matchings as a time-inhomogeneous Markov chain.
