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likelihood-free nested sampling

April 11, 2022

Last week, I came by chance across a paper by Jan Mikelson and Mustafa Khammash on a likelihood-free version of nested sampling (a popular keyword on the ‘Og!). Published in 2020 in PLoS Comput Biol. The setup is a parameterised and hidden state-space model, which allows for an approximation of the (observed) likelihood function L(θ|y) […]

nested sampling: any prior anytime?!

March 26, 2021

A recent arXival by Justin Alsing and Will Handley on “nested sampling with any prior you like” caught my attention. If only because I was under the impression that some priors would not agree with nested sampling. Especially those putting positive weight on some fixed levels of the likelihood function, as well as improper priors. […]

nested sampling X check

September 18, 2020

Andrew Fowlie, Will Handley and Liangliang Su have recently arXived a new paper on checking the convergence of nested sampling by a uniformity test. The argument goes as follows: if the draw from the prior under the likelihood restriction (at the core of the nested sampling principle) is correctly generated, the rank of the realised […]

Nested Sampling SMC [a reply]

April 9, 2020

Here is a response from Robert Salomone following my comments of the earlier day (and pointing out I already commented the paper two years ago): You may be interested to know that we are at the tail end of carrying out a major revision of the paper, which we hope will be done in the […]

nested sampling via SMC

April 2, 2020

“We show that by implementing a special type of [sequential Monte Carlo] sampler that takes two im-portance sampling paths at each iteration, one obtains an analogous SMC method to [nested sampling] that resolves its main theoretical and practical issues.” A paper by Queenslander Robert Salomone, Leah South, Chris Drovandi and Dirk Kroese that I had […]