Multiple non linear equations with shared parameters in brms

I am trying to perform a multivariate analysis with three responses variables where each response variable has its own formula. But the three formulas shared parameters. I want to perform a Bayesian inference that results in one posterior distribution for each parameter. However, using brms I am obtaining one posterior distribution for each parameter for each response variable. How can I perform the bayesian inference obtaining just one posterior distribution?

I tried with:

for_tot<-bf(Vo~((VmaxGK4K6GTP^2)+(VmaxdGK2K4GTPdGTP))/((K1K2K4K6)+(K2K4K6GTP)+(K4K6GTP^2)+(K2K4K5dGTP)+(K2K5dGTP^2)+(K2K4GTPdGTP)),
VmaxG+VmaxdG+K1+K2+K4+K5+K6~1,
nl=TRUE)
for_cyc<-bf(Vo_cyc~((VmaxG
K4K6GTP^2))/((K1K2K4K6)+(K2K4K6GTP)+(K4K6GTP^2)+(K2K4K5dGTP)+(K2K5dGTP^2)+(K2K4GTPdGTP)),
VmaxG+K1+K2+K4+K5+K6~1,
nl=TRUE)
for_lin<-bf(Vo_lin~((VmaxdGK2K4GTPdGTP))/((K1K2K4K6)+(K2K4K6GTP)+(K4K6GTP^2)+(K2K4K5dGTP)+(K2K5dGTP^2)+(K2K4GTPdGTP)),
VmaxdG+K1+K2+K4+K5+K6~1,
nl=TRUE)
form_two<-mvbf(for_cyc,for_lin,for_tot)

But this results in three distributions by parameters.

Thank you very much in advance for your help,

This is unfortunately not yet possible but will tentatively be possible at some point this year. The reason for it not yet being possible is that the required changes will break backwards compatibility in a relevant way and so will have to go into brms 3.0.

Is it possible to perform this using Rstan?

Thank you for your answer,

Santiago

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