t_sample

sherpa.astro.ui.t_sample(num=1, dof=None, id: IdType | None = None, otherids: Sequence[IdType] = (), numcores=None)

Sample the fit statistic by taking the parameter values from a Student’s t-distribution.

For each iteration (sample), change the thawed parameters by drawing values from a Student’s t-distribution, and calculate the fit statistic.

Parameters:

  • num (int, optional) – The number of samples to use (default is 1).

  • dof (optional) – The number of degrees of freedom to use (the default is to use the number from the current fit).

  • id (int, str, or None, optional) – The data set that provides the data. If not given then all data sets with an associated model are used simultaneously.

  • otherids (sequence of int or str, optional) – Other data sets to use in the calculation.

  • numcores (optional) – The number of CPU cores to use. The default is to use all the cores on the machine.

Returns:

A NumPy array table with the first column representing the statistic and later columns the parameters used.

Return type:

samples

See also

fit

Fit a model to one or more data sets.

normal_sample

Sample from the normal distribution.

set_model

Set the source model expression for a data set.

set_stat

Set the statistical method.

uniform_sample

Sample from a uniform distribution.

Examples

The model fit to the default data set has three free parameters. The median value of the statistic calculated by t_sample is returned:

>>> ans = t_sample(num=10000)
>>> ans.shape
(1000, 4)
>>> np.median(ans[:,0])
119.9764357725326