AdaMet: Adaptive Metropolis for Bayesian Analysis
Project description
Adaptive Metropolis for Bayesian Analysis
AdaMet is a well-tested Python implementation of the Adaptive Metropolis algorithm by Haario H., Saksman E., Tamminen J., (2001). It was used in a number of published papers in the astrophysics literature.
Attribution
If you use this software for your research, please cite Cappellari et al. (2013a) where the implementation was introduced. The BibTeX entry for the paper is:
@ARTICLE{Cappellari2013a, author = {{Cappellari}, M. and {Scott}, N. and {Alatalo}, K. and {Blitz}, L. and {Bois}, M. and {Bournaud}, F. and {Bureau}, M. and {Crocker}, A.~F. and {Davies}, R.~L. and {Davis}, T.~A. and {de Zeeuw}, P.~T. and {Duc}, P.-A. and {Emsellem}, E. and {Khochfar}, S. and {Krajnovi{\'c}}, D. and {Kuntschner}, H. and {McDermid}, R.~M. and {Morganti}, R. and {Naab}, T. and {Oosterloo}, T. and {Sarzi}, M. and {Serra}, P. and {Weijmans}, A.-M. and {Young}, L.~M.}, title = "{The ATLAS$^{3D}$ project - XV. Benchmark for early-type galaxies scaling relations from 260 dynamical models: mass-to-light ratio, dark matter, Fundamental Plane and Mass Plane}", journal = {MNRAS}, eprint = {1208.3522}, year = 2013, volume = 432, pages = {1709-1741}, doi = {10.1093/mnras/stt562} }
Installation
install with:
pip install adamet
Without writing access to the global site-packages directory, use:
pip install --user adamet
Documentation
See adamet/examples
License
Copyright (c) 2012-2018 Michele Cappellari
This software is provided as is without any warranty whatsoever. Permission to use, for non-commercial purposes is granted. Permission to modify for personal or internal use is granted, provided this copyright and disclaimer are included in all copies of the software. All other rights are reserved. In particular, redistribution of the code is not allowed.
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