The RooStats Project
Abstract
RooStats is a project to create advanced statistical tools required for the analysis of LHC data, with emphasis on discoveries, confidence intervals, and combined measurements. The idea is to provide the major statistical techniques as a set of C++ classes with coherent interfaces, so that can be used on arbitrary model and datasets in a common way. The classes are built on top of the RooFit package, which provides functionality for easily creating probability models, for analysis combinations and for digital publications of the results. We will present in detail the design and the implementation of the different statistical methods of RooStats. We will describe the various classes for interval estimation and for hypothesis test depending on different statistical techniques such as those based on the likelihood function, or on frequentists or bayesian statistics. These methods can be applied in complex problems, including cases with multiple parameters of interest and various nuisance parameters.
Cite
@article{arxiv.1009.1003,
title = {The RooStats Project},
author = {Lorenzo Moneta and Kevin Belasco and Kyle Cranmer and Sven Kreiss and Alfio Lazzaro and Danilo Piparo and Gregory Schott and Wouter Verkerke and Matthias Wolf},
journal= {arXiv preprint arXiv:1009.1003},
year = {2011}
}
Comments
11 pages, 3 figures, ACAT2010 Conference Proceedings