Adapt MCMC tutorial
"\n",
" # dataset.likelihood returns Cash statistics values\n",
" # emcee will maximisise the LogLikelihood so we need -dataset.likelihood\n",
- " total_lnprob = -dataset.likelihood(None) + lnprob_priors\n",
+ " total_lnprob = -dataset.likelihood() + lnprob_priors\n",
"\n",
" if verb:\n",
" print(\"Parameters are:\", pars)\n",
"dataset.parameters[\"lambda_\"].value = 0.05\n",
"\n",
"print(dataset.model)\n",
- "print(\"LL =\", dataset.likelihood(dataset.parameters))"
+ "print(\"log(L) =\", dataset.likelihood())"
]
},
{
