
In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008−57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.
High Energy Astrophysical Phenomena (astro-ph.HE), Data analysis, FOS: Physical sciences, Multiple datasets, Engineering (General). Civil engineering (General), 004, X-rays: binaries, Methods: data analysis, Física Aplicada, TA1-2040, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
High Energy Astrophysical Phenomena (astro-ph.HE), Data analysis, FOS: Physical sciences, Multiple datasets, Engineering (General). Civil engineering (General), 004, X-rays: binaries, Methods: data analysis, Física Aplicada, TA1-2040, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
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