Cargando…

pyhf: pure-python HistFactory -- the tutorial

<!--HTML-->The HistFactory p.d.f. template [CERN-OPEN-2012-016][1] is per-se independent of its implementation in ROOT and sometimes, it’s useful to be able to run statistical analysis outside of ROOT, RooFit, RooStats framework. This tutorial will introduce users (who are generally familiar w...

Descripción completa

Detalles Bibliográficos
Autores principales: Stark, Giordon Holtsberg, Heinrich, Lukas Alexander, Feickert, Matthew
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2752552
Descripción
Sumario:<!--HTML-->The HistFactory p.d.f. template [CERN-OPEN-2012-016][1] is per-se independent of its implementation in ROOT and sometimes, it’s useful to be able to run statistical analysis outside of ROOT, RooFit, RooStats framework. This tutorial will introduce users (who are generally familiar with hypothesis testing) to the [`pyhf`][2] python package. Examples using public [HEPData][3] material will be used for asymptotic fits, brazil bands, and pull plots. By the end of the tutorial, users will understand how to find likelihoods on HEPData, how to download and perform hypothesis testing, how to patch in a signal into a background-only pdf, and how to simplify likelihoods. [1]: https://cds.cern.ch/record/1456844 [2]: https://scikit-hep.org/pyhf/ [3]: https://www.hepdata.net/