Speaker
Dr
Jeanette Miriam Lorenz
(Ludwig-Maximilians-Univ. Muenchen (DE))
Description
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
fit to data and interpreted with statistical tests.
Internally HistFitter uses the statistics packages RooStats and HistFactory.
A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics.
The concepts of control, signal and validation regions are woven into its fabric.
These are progressively treated with statistically rigorous built-in methods.
Being capable of working with multiple models at once that describe the data,
HistFitter introduces an additional level of abstraction that allows for easy bookkeeping,
manipulation and testing of large collections of signal hypotheses.
Finally, HistFitter provides a collection of tools to present results
with publication quality style through a simple command-line interface.
Primary authors
Dr
Aleksej Koutsman
(TRIUMF (CA))
Dr
David Cote
(University of Texas at Arlington (US))
Dr
Geert Jan Besjes
(Niels Bohr Institute, Univ. of Copenhagen)
Dr
Jeanette Miriam Lorenz
(Ludwig-Maximilians-Univ. Muenchen (DE))
Dr
Max Baak
(CERN)
