cosmoabc: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation

23 Apr 2015 E. E. O. Ishida S. D. P. Vitenti M. Penna-Lima J. Cisewski R. S. de Souza A. M. M. Trindade E. Cameron V. C. Busti for the COIN collaboration

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogues... (read more)

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  • COSMOLOGY AND NONGALACTIC ASTROPHYSICS
  • INSTRUMENTATION AND METHODS FOR ASTROPHYSICS