Journal
COMPUTER PHYSICS COMMUNICATIONS
Volume 184, Issue 9, Pages 2214-2220Publisher
ELSEVIER
DOI: 10.1016/j.cpc.2013.04.008
Keywords
Splines; Monte Carlo; Histograms; Maximum likelihood
Funding
- NSF [0636875]
- NSF GRFP
- Directorate For Geosciences
- Division Of Polar Programs [0636875] Funding Source: National Science Foundation
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Detector response to a high-energy physics process is often estimated by Monte Carlo simulation. For purposes of data analysis, the results of this simulation are typically stored in large multi-dimensional histograms, which can quickly become both too large to easily store and manipulate and numerically problematic due to unfilled bins or interpolation artifacts. We describe here an application of the penalized spline technique (Marx and Filers, 1996) [1] to efficiently compute B-spline representations of such tables and discuss aspects of the resulting B-spline fits that simplify many common tasks in handling tabulated Monte Carlo data in high-energy physics analysis, in particular their use in maximum-likelihood fitting. (C) 2013 Elsevier B.V. All rights reserved.
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