Replication data for: "Natural Priors, CMSSM Fits and LHC Weather Forecasts"

MCMC scan of CMSSM used in "Natural Priors, CMSSM Fits and LHC Weather Forecasts". The entry is tabular data with named rows. Minimal analysis is available via the browser. Except from the original web-page that hosted this data. 10 independent files. Each one is a statistically independent sampling of the posterior. The density of points in parameter space is proportional to the posterior probability of the point. The fits are described in the paper, and have had the dark matter, (g-2)_mu, B_s->mu mu, MW, sin^2 theta_l, mt, mb, alphas, BR(b->s gamma) and sparticle/Higgs direct search limits applied to them. Each point in the sample is a line of the file, organised into a list of numbers, in the following order: The weight of the point - you *must* take this into account if you're doing Bayesian stats. An integer specifying the number of parameters to come m0/GeV m12/GeV A0/GeV tan beta mb(mb) MSbar/GeV mt/GeV alpha_s(MZ) MSbar/GeV alpha(MZ) MSbar sign mu m_gluino/GeV m_chargino1/GeV mstau_1/GeV mselectron_R/GeV msquark_L/GeV mstop_1/GeV msbottom_1/GeV msneutrino_1/GeV mh^0/GeV mA/GeV omega_{DM} h^2 (g-2)_mu BR(b->s gamma) m_neutralino_1/GeV BR(B_s->mu mu) m_neutralino_2/GeV sin^2 theta_l^(eff) MW/GeV irrelevant irrelevant irrelevant irrelevant sigma(LHC QCD sparticle production)/pb sigma(LHC gaugino production)/pb sigma(LHC slepton production)/pb mu parameter/GeV m3squared parameter/GeV^2 ln(posterior) (overall normalisation)