Sorry for the late reply!
This is the original model with three likelihoods (where ‘p’, ‘keq’, ‘R’, ‘T_Bottom’ and ‘r’ are the experimental data), and the equations in the red block is the model I want to simulated, but my professor said that the MCMC model should have only one likelihood.
As a result of which, I try to use np.hstack to combine three ‘r’ into one array as follow:
with XF_model_PL:
r_CH4_obs = - r_2 - r_3
r_CO2_obs = r_1 + r_2
r_CO_obs = r_3 - r_1
rrr_obs = np.hstack((r_CH4_obs,r_CO_obs,r_CO2_obs))
rrr_likelihood = pm.Normal('rrr_likelihood',mu = rrr_obs, sd = sigma, observed = rrr0)
As a result of which, Python encounted the error of ‘setting an array element with a sequence.’
So I want to ask for help that how to construct a likelihood function with a vector or matrix to complete the MCMC sampling. Also I would like to find some reference material or literature on this to simulate different multiple likelihood models with MCMC methods. Thanks!