Abstract
HistFitter is a software framework for statistical data analysis that has been used extensively in the ATLAS Collaboration to analyze data of proton-proton collisions produced by the Large Hadron Collider at CERN. Most notably, HistFitter has become a de-facto standard in searches for supersymmetric particles since 2012, with some usage for Exotic and Higgs boson physics. HistFitter coherently combines several statistics tools in a programmable and flexible framework that is capable of bookkeeping hundreds of data models under study using thousands of generated input histograms.HistFitter interfaces with the statistics tools HistFactory and RooStats to construct parametric models and to perform statistical tests of the data, and extends these tools in four key areas. The key innovations are to weave the concepts of control, validation and signal regions into the very fabric of HistFitter, and to treat these with rigorous methods. Multiple tools to visualize and interpret the results through a simple configuration interface are also provided.
Highlights
HistFitter is a software framework for statistical data analysis that has been used extensively in the ATLAS Collaboration to analyze data of proton-proton collisions produced by the Large Hadron Collider at CERN
HistFitter [1] is a software framework for statistical data analysis extensively used in the ATLAS Collaboration [2] in searches for supersymmetric particles, in which data of protonproton collisions produced by the Large Hadron Collider at CERN are analyzed
Summary We have presented HistFitter, a software framework for statistical analyses
Summary
This content has been downloaded from IOPscience. Please scroll down to see the full text. Ser. 664 072004 (http://iopscience.iop.org/1742-6596/664/7/072004) View the table of contents for this issue, or go to the journal homepage for more. Download details: IP Address: 137.138.93.202 This content was downloaded on 09/03/2016 at 08:03 Please note that terms and conditions apply. 21st International Conference on Computing in High Energy and Nuclear Physics (CHEP2015) IOP Publishing. Journal of Physics: Conference Series 664 (2015) 072004 doi:10.1088/1742-6596/664/7/072004
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