Title: Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation,
Abstract: We introduce dynamic nested sampling: a generalisation of the nested sampling
algorithm in which the number of "live points" varies to allocate samples more
efficiently. In empirical tests the new method significantly improves
calculation accuracy compared to standard nested sampling with the same number
of samples; this increase in accuracy is equivalent to speeding up the
computation by factors of up to ~72 for parameter estimation and ~7 for
evidence calculations. We also show that the accuracy of both parameter
estimation and evidence calculations can be improved simultaneously. In
addition, unlike in standard nested sampling, more accurate results can be
obtained by continuing the calculation for longer. Popular standard nested
sampling implementations can be easily adapted to perform dynamic nested
sampling, and several dynamic nested sampling software packages are now
publicly available.