Custom Orthogonal Weight functions (COWs) for event classification

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, vol. 1040, pp. 167270

Abstract

A common problem in data analysis is the separation of signal and background. We revisit and generalise the so-called sWeights method, which allows one to calculate an empirical estimate of the signal density of a control variable using a fit of a mixed signal and background model to a discriminating variable. We show that sWeights are a special case of a larger class of Custom Orthogonal Weight functions (COWs), which can be applied to a more general class of problems in which the discriminating and control variables are not necessarily independent and still achieve close to optimal performance. We also investigate the properties of parameters estimated from fits of statistical models to sWeighted data and provide closed formulas for the asymptotic covariance matrix of the fitted parameters. To illustrate our findings, we discuss several practical applications of these techniques.

Authors 3

1. H.-P. Dembinski

   TU Dortmund University

   Affiliation as printed

   TU Dortmund, Germany

2. Christoph Langenbruch Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen, Germany

3. MICHAEL SCHMELLING

   Max Planck Institute for Nuclear Physics

   Affiliation as printed

   Max Planck Institute for Nuclear Physics, Heidelberg, Germany