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[ascl:2104.006] RJObject: Reversible Jump Objects

RJObject provides a general approach to trans-dimensional Bayesian inference problems, using trans-dimensional MCMC embedded within a Nested Sampling algorithm. This allows exploration of the posterior distribution and calculattion of the marginal likelihood (summed over N) even if the problem contains a phase transition or other difficult features such as multimodality.

Code site:
https://github.com/eggplantbren/RJObject
Used in:
https://ui.adsabs.harvard.edu/abs/2018ApJ...854..141D
Described in:
http://adsabs.harvard.edu/abs/2014arXiv1411.3921B
Bibcode:
2021ascl.soft04006B

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ascl:2104.006
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