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CITATION.cff
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cff-version: 1.2.0
message: "Please cite the following works when using this software."
type: software
authors:
- family-names: "Heinrich"
given-names: "Lukas"
orcid: "https://orcid.org/0000-0002-4048-7584"
affiliation: "CERN"
- family-names: "Feickert"
given-names: "Matthew"
orcid: "https://orcid.org/0000-0003-4124-7862"
affiliation: "University of Illinois at Urbana-Champaign"
- family-names: "Stark"
given-names: "Giordon"
orcid: "https://orcid.org/0000-0001-6616-3433"
affiliation: "SCIPP, University of California, Santa Cruz"
title: "pyhf: v0.6.3"
version: 0.6.3
doi: 10.5281/zenodo.1169739
repository-code: "https://github.com/scikit-hep/pyhf/releases/tag/v0.6.3"
url: "https://pyhf.readthedocs.io/en/v0.6.3/"
keywords:
- python
- physics
- statistics
- fitting
- scipy
- numpy
- tensorflow
- pytorch
- jax
- auto-differentiation
license: "Apache-2.0"
abstract: |
The HistFactory p.d.f. template is per-se independent of its implementation
in ROOT and it is useful to be able to run statistical analysis outside of
the ROOT, RooFit, RooStats framework. pyhf is a pure-python implementation
of that statistical model for multi-bin histogram-based analysis and its
interval estimation is based on the asymptotic formulas of "Asymptotic
formulae for likelihood-based tests of new physics". pyhf supports modern
computational graph libraries such as TensorFlow, PyTorch, and JAX in order
to make use of features such as autodifferentiation and GPU acceleration.
references:
- type: article
authors:
- family-names: "Heinrich"
given-names: "Lukas"
orcid: "https://orcid.org/0000-0002-4048-7584"
affiliation: "CERN"
- family-names: "Feickert"
given-names: "Matthew"
orcid: "https://orcid.org/0000-0003-4124-7862"
affiliation: "University of Illinois at Urbana-Champaign"
- family-names: "Stark"
given-names: "Giordon"
orcid: "https://orcid.org/0000-0001-6616-3433"
affiliation: "University of Illinois at Urbana-Champaign"
- family-names: "Cranmer"
given-names: "Kyle"
orcid: "https://orcid.org/0000-0002-5769-7094"
affiliation: "New York University"
title: "pyhf: pure-Python implementation of HistFactory statistical models"
doi: 10.21105/joss.02823
url: "https://doi.org/10.21105/joss.02823"
year: 2021
publisher:
name: "The Open Journal"
volume: 6
number: 58
pages: 2823
journal: Journal of Open Source Software