set_stat

sherpa.astro.ui.set_stat(stat: str | Stat) → None

Set the statistical method.

Changes the method used to evaluate the fit statistic, that is the numerical measure that determines how closely the model represents the data.

Parameters:

stat (str or sherpa.stats.Stat instance) – When a string, the name of the statistic (case is not important): see list_stats() for supported values. Otherwise an instance of the statistic to use.

Raises:

sherpa.utils.err.ArgumentErr – If the stat argument is not recognized.

See also

calc_stat

Calculate the statistic value for a dataset.

get_stat_name

Return the current statistic method.

list_stats

List the supported fit statistics.

load_user_stat

Create a user-defined statistic.

Notes

The available statistics include:

cash

A maximum likelihood function [1].

chi2

Chi-squared statistic using the supplied error values.

chi2constvar

Chi-squared with constant variance computed from the counts data.

chi2datavar

Chi-squared with data variance. If the data has 0 counts then the error for that bin is 0.

chi2gehrels

Chi-squared with gehrels method [2]. This is the default method.

chi2modvar

Chi-squared with model amplitude variance.

chi2xspecvar

Chi-squared with data variance to match XSPEC. Errors from zero-count channels (source or background) are ignored if the other channel (background or source) contains counts, or replaced by a minimum value (when both source or background are empty). It should not be used when a model is fit to the background rather than the background is subtracted from the data.

cstat

A maximum likelihood function (the XSPEC implementation of the Cash function) [3]. This does not include support for including the background.

wstat

A maximum likelihood function which includes the background data as part of the fit (i.e. for when it is not being explicitly modelled) (the XSPEC implementation of the Cash function) [3].

leastsq

The least-squares statisic (the error is not used in this statistic).

References

  1. Cash, W. “Parameter estimation in astronomy through application of the likelihood ratio”, ApJ, vol 228, p. 939-947 (1979).

  2. Gehrels, N. “Confidence limits for small numbers of events in astrophysical data”, ApJ, vol 303, p. 336-346 (1986).

  3. https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSappendixStatistics.html

Examples

>>> set_stat('cash')