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Skilling, J., AIP Conference Proceedings 735
Original
2004
Earlier work this paper cites.
Shaw, J. R., Bridges, M., & Hobson, M. P., MNRAS 378
2007
Earlier work this paper cites.

Similar

Feroz, F. & Hobson, M. P., MNRAS 384
2008
Cited alongside, same era.
Feroz, F., Hobson, M. P., & Bridges, M., MNRAS 398
2009
Cited alongside, same era.

Then

Handberg, R. & Campante, T. L., A&A 527
2011
Later among the works it cites.
Corsaro E. & De Ridder J., A&A 571
2014
Later among the works it cites.

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2015

DIAMONDS: A new Bayesian nested sampling tool

Corsaro, Enrico, De Ridder, Joris

Understand

In the context of high-quality asteroseismic data provided by the NASA Kepler mission, we developed a new code, termed Diamonds (high-DImensional And multi-MOdal NesteD Sampling), for fast Bayesian parameter estimation and model comparison by means of the Nested Sampling Monte Carlo (NSMC) algorithm, an efficient and powerful method very suitable for high-dimensional problems (like the peak bagging analysis of solar-like oscillations) and multi-modal problems (i.e.

problems that show multiple solutions).
We applied the code to the peak bagging analysis of solar-like oscillations observed in a challenging F-type star.
By means of Diamonds one is able to detect the different backgrounds in the power spectrum of the star (e.g.