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  • Installation
  • Intro
  • Configuration
  • Logging and Verbosity
  • Notes for XSPEC Users
  • Minimization
  • Bayesian Posterior Sampling
  • Bayesian Sampler Examples
  • Plugins
  • Modeling
  • Frequently Asked Questions
  • API
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Features and examples:

  • Analysis Results
  • Random Variates
  • Point source plotting basics
  • Constructing plugins from TimeSeries
  • Analyzing GRB 080916C
  • Fitting XMM-Newton data with the APEC model
  • Example joint fit between GBM and Swift BAT
  • Joint fitting XRT and GBM data with XSPEC models
  • Point Source Fluxes and Multiple Sources
  • Fermi-LAT via FermiPyLike
  • Analysis of GRB 190114C with Fermi-LAT
  • Time-energy fit
  • Generating Synthetic Data
  • Goodness of Fit and Model Comparison
The Multi-Mission Maximum Likelihood framework
  • API
  • threeML package
  • threeML.utils package
  • threeML.utils.statistics package

threeML.utils.statistics package

Submodules

  • threeML.utils.statistics.gammaln module
  • threeML.utils.statistics.likelihood_functions module
    • half_chi2()
    • poisson_log_likelihood_ideal_bkg()
    • poisson_observed_gaussian_background()
    • poisson_observed_poisson_background()
    • poisson_observed_poisson_background_xs()
    • regularized_log()
    • xlogy()
    • xlogy_one()
  • threeML.utils.statistics.stats_tools module
    • PoissonResiduals
      • PoissonResiduals.significance_one_side()
    • Significance
      • Significance.Noff
      • Significance.Non
      • Significance.alpha
      • Significance.expected
      • Significance.gaussian_background()
      • Significance.known_background()
      • Significance.li_and_ma()
      • Significance.li_and_ma_equivalent_for_gaussian_background()
      • Significance.net
    • aic()
    • bic()
    • dic()
    • sqrt_sum_of_squares()
    • waic()

Module contents

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