  The standard Bayesian technique for searching pulsar timing data for
gravitational wave (GW) bursts with memory (BWMs) using Markov Chain Monte
Carlo (MCMC) sampling is very computationally expensive to perform. In this
paper, we explain the implementation of an efficient Bayesian technique for
searching for BWMs. This technique makes use of the fact that the signal model
for Earth-term BWMs (BWMs passing over the Earth) is fully factorizable. We
estimate that this implementation reduces the computational complexity by a
factor of 100. We also demonstrate that this technique gives upper limits
consistent with published results using the standard Bayesian technique, and
may be used to perform all of the same analyses that standard MCMC techniques
can perform.
