  Randomized quasi-Monte Carlo (RQMC) sampling can bring orders of magnitude
reduction in variance compared to plain Monte Carlo (MC) sampling. The extent
of the efficiency gain varies from problem to problem and can be hard to
predict. This article presents an R function rhalton that produces scrambled
versions of Halton sequences. On some problems it brings efficiency gains of
several thousand fold. On other problems, the efficiency gain is minor. The
code is designed to make it easy to determine whether a given integrand will
benefit from RQMC sampling. An RQMC sample of n points in $[0,1]^d$ can be
extended later to a larger n and/or d.
