t_sample¶
-
sherpa.sim.sample.
t_sample
(fit, num=1, dof=2, numcores=None)[source] [edit on github]¶ 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: - fit – The fit results.
- 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).
- 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
normal_sample()
- Sample from the normal distribution.
uniform_sample()
- Sample from a uniform distribution.