On the use of C-stat in testing models for X-ray spectra
By J. Kaastra. 2017
142 citations recorded by the source corpus.
It has been shown that for the analysis of X-ray spectra the C-statistic, contrary to the chi^2-statistic, provides unbiased estimates of the model parameters and their uncertainty ranges. However, it is often stated that the C-statistic cannot be used to carry out statistical tests on the goodness of fit of the model, and therefore several investigations are still based on chi^2-statistics. Here we show that it is straightforward to calculate the expected value and variance of the C-statistic so that it can be used in tests. We provide formulae and simple numerical approximations to evaluate these expected values and variances. We also give examples indicating that tests based on only the expected value and variance of the C-statistic are reliable for spectra even with only ~30 counts. Therefore the C-statistic can be used for statistical tests such as assessing the goodness of fit of a spectral model.
Subfields: Applied Mathematics, Radiation, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/7db8e0f2c65e72868a17c7d4a8e4d8df19853b99
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In Applied Mathematics
In Radiation
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Citations in the corpus
- Cluster Cosmology Constraints from the 2500 deg2 SPT-SZ Survey: Inclusion of Weak Gravitational Lensing Data from Magellan and the Hubble Space Telescope (2018, methodology): “…in each bin are too small to apply Gaussian χ2 statistics, and we estimate the goodness of fit using a prescription for the Poisson statistic (Kaastra 2017).55 This approach is similar to our likelihood analysis, which applies Poisson statistics within infinitesimally small bins, instead of…”