HistFitter software framework for statistical data analysis
M. Baak, G.J. Besjes, D. Cote, A. Koutsman, J. Lorenz, D. Short

TL;DR
HistFitter is a flexible, object-oriented software framework used by the ATLAS Collaboration for statistical analysis of large datasets from the LHC, enabling complex data modeling, fitting, and result presentation.
Contribution
It introduces a novel, core-analysis-inspired design that simplifies building, fitting, and interpreting complex data models with multiple hypotheses in particle physics.
Findings
Widely used in ATLAS supersymmetry searches since 2012
Supports multiple data models simultaneously with high abstraction
Provides publication-quality result presentation tools
Abstract
We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
