HistFitter software framework for statistical data analysis

被引：159

作者：

Baak, M. ^{[1
]}

Besjes, G. J. ^{[2
,3
]}

Cote, D. ^{[4
]}

Koutsman, A. ^{[5
]}

Lorenz, J. ^{[6
,7
]}

Short, D. ^{[8
]}

机构：

[1] CERN, Geneva, Switzerland

[2] Radboud Univ Nijmegen, NL-6525 ED Nijmegen, Netherlands

[3] Nikhef, Amsterdam, Netherlands

[4] Univ Texas Arlington, Arlington, TX USA

[5] TRIUMF, Vancouver, BC V6T 2A3, Canada

[6] Univ Munich, Munich, Germany

[7] Excellence Cluster Universe, Garching, Germany

[8] Univ Oxford, Oxford, England

来源：

EUROPEAN PHYSICAL JOURNAL C | 2015年 / 75卷 / 04期

基金：

美国国家科学基金会; 加拿大自然科学与工程研究理事会;

关键词：

Big data - Data handling - Information analysis - Object oriented programming - Statistical mechanics - Statistics;

D O I：

10.1140/epjc/s10052-015-3327-7

中图分类号：

O412 [相对论、场论]; O572.2 [粒子物理学];

学科分类号：

摘要：

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.

引用

页码：1 / 20

页数：20

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