The sherpa.sim.sample module

Classes

NormalParameterSampleFromScaleMatrix()
NormalParameterSampleFromScaleVector()
NormalSampleFromScaleMatrix()
NormalSampleFromScaleVector()
ParameterSampleFromScaleMatrix()
ParameterSampleFromScaleVector()
ParameterScale()
ParameterScaleMatrix()
ParameterScaleVector()
StudentTParameterSampleFromScaleMatrix()
StudentTSampleFromScaleMatrix()
UniformParameterSampleFromScaleVector()
UniformSampleFromScaleVector()

Functions

multivariate_t(mean, cov, df[, size]) Draw random deviates from a multivariate Student’s T distribution Such a distribution is specified by its mean covariance matrix, and degrees of freedom.
multivariate_cauchy(mean, cov[, size]) This needs to be checked too! A reference to the literature the better
normal_sample(fit[, num, sigma, correlate, …]) Sample the fit statistic by taking the parameter values from a normal distribution.
uniform_sample(fit[, num, factor, numcores]) Sample the fit statistic by taking the parameter values from an uniform distribution.
t_sample(fit[, num, dof, numcores]) Sample the fit statistic by taking the parameter values from a Student’s t-distribution.

Class Inheritance Diagram

Inheritance diagram of ParameterScale, ParameterScaleVector, ParameterScaleMatrix, ParameterSampleFromScaleMatrix, ParameterSampleFromScaleVector, UniformParameterSampleFromScaleVector, NormalParameterSampleFromScaleVector, NormalParameterSampleFromScaleMatrix, StudentTParameterSampleFromScaleMatrix, NormalSampleFromScaleMatrix, NormalSampleFromScaleVector, UniformSampleFromScaleVector, StudentTSampleFromScaleMatrix