BAT - The Bayesian Analysis Toolkit

By Allen Caldwell, Daniel Kollár, Kevin Kröninger. Computer Physics Communications, 2008

334 citations recorded by the source corpus.

Bayesian Analysis Toolkit (BAT) is a new toolkit for data analysis based on Bayes' Theorem. BAT is realized with the use of Markov Chain Monte Carlo which gives access to the full posterior probability distribution. Parameter estimation, limit setting and uncertainty propagation are implemented in a straightforward manner. The tool allows to compare models and to estimate the goodness-of-fit using well-established methods.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b1e6cb1819894a2217e0f76152123f2349515a86

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Atlas Collaboration
2. Cms Collaboration
3. Gudrun Heinrich
4. John Ellis
5. T. You
6. Veronica Sanz
7. G. Panico
8. Stefan Prestel

In Statistics and Probability

1. M. Fedele
2. John Ellis
3. M. Valli
4. Marco Ciuchini
5. L. Silvestrini
6. Ayan Paul
7. Atlas Collaboration
8. E. Franco

Citations in the corpus

• Electroweak precision observables, new physics and the nature of a 126 GeV Higgs boson (2013, methodology): “To obtain our results, we perform a Bayesian analysis using the BAT library [21] and our own implementation of the EWPO formulæ.”
• Higgs Physics at the HL-LHC and HE-LHC (2019, methodology): “The default fit procedure, which we use here, follows a Bayesian statistical approach and uses BAT (Bayesian Analysis Toolkit) [782].”
• Electroweak precision observables and Higgs-boson signal strengths in the Standard Model and beyond: present and future (2016, methodology): “Exploiting the Markov-Chain MonteCarlo implementation provided in the Bayesian Analysis Toolkit (BAT) [10], HEPfit can be used as a standalone program to perform Bayesian statistical analyses.”
• Search for new high-mass phenomena in the dilepton final state using 36 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}$ = 13 TeV with the ATLAS detector (2017, methodology): “The calculations are performed with the Bayesian Analysis Toolkit (BAT) [53], which uses a Markov Chain MC – 14 –”
• B → K∗ℓ+ℓ− decays at large recoil in the Standard Model: a theoretical reappraisal (2015, methodology): “For uncorrelated observables, such as (4)HEPfit uses a parallelized version of the Bayesian Analysis Toolkit (BAT) library [58] to perform MCMC runs.”