http://arxiv.org/abs/2212.01760
We present a method for improving the performance of nested
sampling as well as its accuracy. Building on previous work by
Chen et al., we show that posterior repartitioning
may be used to reduce the amount of time nested sampling spends in
compressing from prior to posterior if a suitable “proposal”
distribution is supplied. We showcase this on a cosmological example
with a Gaussian posterior, and release the code as an LGPL licensed,
extensible Python package
https://gitlab.com/a-p-petrosyan/sspr.
A. Petrosyan and W. Handley
Tue, 6 Dec 22
18/87
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