MH¶
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class
sherpa.sim.mh.
MH
(fcn, sigma, mu, dof, *args)[source] [edit on github]¶ Bases:
sherpa.sim.mh.Sampler
The Metropolis Hastings Sampler
Methods Summary
accept
(current, current_stat, proposal, …)Should the proposal be accepted (using the Cash statistic and the t distribution)? accept_mh
(current, current_stat, proposal, …)calc_fit_stat
(proposed_params)calc_stat
(proposed_params)dmvt
(x[, log, norm])draw
(current)Create a new set of parameter values using the t distribution. init
([log, inv, defaultprior, priorshape, …])mh
(current)MH jumping rule reject
()tear_down
()update
(stat, mu[, init])include prior Methods Documentation
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accept
(current, current_stat, proposal, proposal_stat, **kwargs)[source] [edit on github]¶ Should the proposal be accepted (using the Cash statistic and the t distribution)?
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accept_mh
(current, current_stat, proposal, proposal_stat)[source] [edit on github]¶
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calc_fit_stat
(proposed_params)[source] [edit on github]¶
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calc_stat
(proposed_params)[source] [edit on github]¶
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dmvt
(x, log=True, norm=False)[source] [edit on github]¶
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draw
(current)[source] [edit on github]¶ Create a new set of parameter values using the t distribution.
Given the best-guess (mu) and current (current) set of parameters, along with the covariance matrix (sigma), return a new set of parameters.
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init
(log=False, inv=False, defaultprior=True, priorshape=False, priors=(), originalscale=True, scale=1, sigma_m=False)[source] [edit on github]¶
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mh
(current)[source] [edit on github]¶ MH jumping rule
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reject
()[source] [edit on github]¶
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tear_down
()[source] [edit on github]¶
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update
(stat, mu, init=True)[source] [edit on github]¶ include prior
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