Handling uncertainties in background shapes: the discrete profiling method

Autor:	Dauncey, P. D., Kenzie, M., Wardle, N., Davies, G. J.
Rok vydání:	2014
Předmět:	Physics - Data Analysis Statistics and Probability High Energy Physics - Experiment
Druh dokumentu:	Working Paper
DOI:	10.1088/1748-0221/10/04/P04015
Popis:	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. Comment: Accepted by J.Inst
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1408.6865 Zobrazit plný text záznamu View this record from Arxiv