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arXiv · 1408.6865

Handling uncertainties in background shapes: the discrete profiling method

P. D. Dauncey·M. Kenzie·N. Wardle·G. J. Davies
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Abstract

A common problem in data analysis is that the functional form, as well as the parameter values, of the underlying model which should describe a dataset is not known a priori. In these cases some extra uncertainty must be assigned to the extracted parameters of interest due to lack of exact knowledge of the functional form of the model. A method for assigning an appropriate error is presented. The method is based on considering the choice of functional form as a discrete nuisance parameter which is profiled in an analogous way to continuous nuisance parameters. The bias and coverage of this method are shown to be good when applied to a realistic example.

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P. D. Dauncey, M. Kenzie, N. Wardle, G. J. Davies. 2014-08-28. Handling uncertainties in background shapes: the discrete profiling method. https://doi.org/10.1088/1748-0221/10/04/p04015

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