Superplot: a graphical interface for plotting and analysing MultiNest output

Abstract.We present an application, Superplot, for calculating and plotting statistical quantities relevant to parameter inference from a “chain” of samples drawn from a parameter space, produced by, e.g., MultiNest. A simple graphical interface allows one to browse a chain of many variables quickly, and make publication quality plots of, inter alia, one- and two-dimensional profile likelihood, posterior pdf (with kernel density estimation), confidence intervals and credible regions. In this short manual, we document installation and basic usage, and define all statistical quantities and conventions. The code is fully compatible with Linux and Windows. All functionality is available on Mac OSX, though it must be invoked by the command line rather than a graphical interface.

[1]  R. Trotta,et al.  A Markov chain Monte Carlo analysis of the CMSSM , 2006, hep-ph/0602028.

[2]  Farhan Feroz,et al.  SuperBayeS: Supersymmetry Parameters Extraction Routines for Bayesian Statistics , 2011 .

[3]  Saba Sehrish,et al.  CosmoSIS: Modular cosmological parameter estimation , 2014, Astron. Comput..

[4]  P. J. Green,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[5]  Hiranya V. Peiris,et al.  Bayesian Analysis of Inflation: Parameter Estimation for Single Field Models , 2011 .

[6]  F. James.  Statistical Methods in Experimental Physics , 1973 .

[7]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[8]  P. Gregory.  Bayesian Logical Data Analysis for the Physical Sciences: The how-to of Bayesian inference , 2005 .

[9]  D. W. Scott,et al.  Multivariate Density Estimation, Theory, Practice and Visualization , 1992 .

[10]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[11]  Richard Easther,et al.  Bayesian Analysis of Inflation II: Model Selection and Constraints on Reheating , 2011, 1112.0326.

[12]  Antony Lewis,et al.  Efficient sampling of fast and slow cosmological parameters , 2013, 1304.4473.

[13]  F. Feroz,et al.  MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics , 2008, 0809.3437.

[14]  Hiranya V. Peiris,et al.  Bayesian Analysis of Inflation III: Slow Roll Reconstruction Using Model Selection , 2012, 1202.0304.

[15]  S. S. Wilks.  The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses , 1938 .

[16]  J. Marrouche,et al.  The pMSSM10 after LHC run 1 , 2015, The European physical journal. C, Particles and fields.

[17]  R. Tapia,et al.  Nonparametric Function Estimation, Modeling, and Simulation , 1987 .

[18]  A. Lasenby,et al.  polychord: next-generation nested sampling , 2015, 1506.00171.

[19]  Philip C. Gregory,et al.  Bayesian Logical Data Analysis for the Physical Sciences: Acknowledgements , 2005 .

[20]  Fons Rademakers,et al.  ROOT — An object oriented data analysis framework , 1997 .

[21]  Grigor Aslanyan,et al.  Cosmo++: An object-oriented C++ library for cosmology , 2013, Comput. Phys. Commun..

[22]  G. Arfken.  Mathematical Methods for Physicists , 1967 .

[23]  David W. Scott,et al.  Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.

[24]  Pat Scott,et al.  Pippi — Painless parsing, post-processing and plotting of posterior and likelihood samples , 2012, The European Physical Journal Plus.

[25]  A. Merloni,et al.  X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue , 2014, 1402.0004.

[26]  Gaël Varoquaux,et al.  The NumPy Array: A Structure for Efficient Numerical Computation , 2011, Computing in Science & Engineering.

[27]  F. Feroz,et al.  Multimodal nested sampling: an efficient and robust alternative to Markov Chain Monte Carlo methods for astronomical data analyses , 2007, 0704.3704.

[28]  Andy Buckley,et al.  GAMBIT: Global And Modular BSM Inference Tool , 2017 .

[29]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[30]  M. P. Hobson,et al.  polychord: nested sampling for cosmology , 2015, Monthly Notices of the Royal Astronomical Society: Letters.

[31]  J. Skilling.  Nested sampling for general Bayesian computation , 2006 .

[32]  Tim B. Swartz,et al.  Bayesian Analysis of Dyadic Data , 2007 .

[33]  A. Fowlie.  CMSSM, naturalness and the "fine-tuning price" of the Very Large Hadron Collider , 2014, 1403.3407.

[34]  Frank E. Harris,et al.  Mathematical Methods for Physicists: A Comprehensive Guide , 2012 .

[35]  A. Lewis,et al.  Cosmological parameters from CMB and other data: A Monte Carlo approach , 2002, astro-ph/0205436.

[36]  F. Feroz,et al.  Bayes-x: a Bayesian inference tool for the analysis of X-ray observations of galaxy clusters , 2013, 1310.1885.