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pro vyhledávání: '"Cowan , Glen"'
Autor:
Canonero, Enzo, Cowan, Glen
The Gamma Variance Model (GVM) is a statistical model that incorporates uncertainties in the assignment of systematic errors (informally called errors-on-errors). The model is of particular use in analyses that combine the results of several measurem
Externí odkaz:
http://arxiv.org/abs/2407.05322
Publikováno v:
Eur. Phys. J. C 83, 1100 (2023)
We present improved methods for calculating confidence intervals and $p$-values in situations where standard asymptotic approaches fail due to small sample sizes. We apply these techniques to a specific class of statistical model that can incorporate
Externí odkaz:
http://arxiv.org/abs/2304.10574
Autor:
Cranmer, Kyle, Kraml, Sabine, Prosper, Harrison B., Bechtle, Philip, Bernlochner, Florian U., Bloch, Itay M., Canonero, Enzo, Chrzaszcz, Marcin, Coccaro, Andrea, Conrad, Jan, Cowan, Glen, Feickert, Matthew, Iachellini, Nahuel Ferreiro, Fowlie, Andrew, Heinrich, Lukas, Held, Alexander, Kuhr, Thomas, Kvellestad, Anders, Madigan, Maeve, Mahmoudi, Farvah, Morå, Knut Dundas, Neubauer, Mark S., Pierini, Maurizio, Rojo, Juan, Sekmen, Sezen, Silvestrini, Luca, Sanz, Veronica, Stark, Giordon, Torre, Riccardo, Thorne, Robert, Waltenberger, Wolfgang, Wardle, Nicholas, Wittbrodt, Jonas
Publikováno v:
SciPost Phys. 12, 037 (2022)
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing
Externí odkaz:
http://arxiv.org/abs/2109.04981
Autor:
Cowan, Glen
The statistical significance that characterizes a discrepancy between a measurement and theoretical prediction is usually calculated assuming that the statistical and systematic uncertainties are known. Many types of systematic uncertainties are, how
Externí odkaz:
http://arxiv.org/abs/2107.02652
Autor:
Brenner, Lydia, Verschuuren, Pim, Balasubramanian, Rahul, Burgard, Carsten, Croft, Vincent, Cowan, Glen, Verkerke, Wouter
In this paper we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interf
Externí odkaz:
http://arxiv.org/abs/1910.14654
A method to perform unfolding with Gaussian processes (GPs) is presented. Using Bayesian regression, we define an estimator for the underlying truth distribution as the mode of the posterior. We show that in the case where the bin contents are distri
Externí odkaz:
http://arxiv.org/abs/1811.01242
Autor:
Cowan, Glen
Publikováno v:
Eur. Phys. J. C (2019) 79:133
In a statistical analysis in Particle Physics, nuisance parameters can be introduced to take into account various types of systematic uncertainties. The best estimate of such a parameter is often modeled as a Gaussian distributed variable with a give
Externí odkaz:
http://arxiv.org/abs/1809.05778
Autor:
Cowan, Glen
These lectures describe several topics in statistical data analysis as used in High Energy Physics. They focus on areas most relevant to analyses at the LHC that search for new physical phenomena, including statistical tests for discovery and exclusi
Externí odkaz:
http://arxiv.org/abs/1307.2487
We present the asymptotic distribution for two-sided tests based on the profile likelihood ratio with lower and upper boundaries on the parameter of interest. This situation is relevant for branching ratios and the elements of unitary matrices such a
Externí odkaz:
http://arxiv.org/abs/1210.6948
We propose a method for setting limits that avoids excluding parameter values for which the sensitivity falls below a specified threshold. These "power-constrained" limits (PCL) address the issue that motivated the widely used CLs procedure, but do s
Externí odkaz:
http://arxiv.org/abs/1105.3166