Loving ISIS - Confessions of a Former XSPEC User
Systematic Errors and Custom Statistics
ISIS allows a fair amount of flexibility over the way statistics are calculated and errors are propagated. As in XSPEC, you don't have to think about this if you don't want to, but if you do want to, there's several choices that you can make:
set_fit_method("choice"); % Choose minimization method ... load_fit_method("library.so","name"); % ... or create your own set_fit_statistic("choice"); % Choose chi squared or cash ... load_fit_statistic("library.so","name"); % ... or create your own set_rebin_error_hook(id,"name"); % Propagate errors your own wayMost people most of the time seem to be happy with chi squared statistics with error bars defined by Poisson statistics in each data bin (i.e., the ISIS and XSPEC defaults). In this example, a notable exception is for the high count rate PCA statistics, which are dominated by systematic uncertainties.
There are no truly universally accepted and proper ways of dealing with systematic errors. ISIS will treat them essentially the way that XSPEC does. For a given bin, ISIS will calculate the mean input fractional systematic error for that bin. This error will then be added in quadrature to the statistical error. This will happen automatically if systematic errors are defined in the PHA file.
To remove the systematic errors on dataset
set_sys_err_frac(id,NULL);To change the systematic errors on dataset
set_sys_err_frac(id,Double_Type+0.005);(There are 129 data bins in the PCA spectrum.
Important Note about ISIS Statistics
ISIS does set a lower bound to the minimum size
of a statistical error bar (to avoid roundoff errors, etc.). We
violate this lower bound when defining the radio data as a counts/bin
dataset. Thus, we overwrite that choice in my
Minimum_Stat_Err = 1.e-30;
Next up: Backgrounds.
This page was last updated Oct 7, 2013 by Michael Nowak. To comment on it or the material presented here, send email to email@example.com.