Run multiple HMC chains and return a dataframe of parameters
hmc_da(log_posterior, gradient, n_steps, init_parameters, iters, chains = 2)
| log_posterior | a function for the unnormalised log-posterior from parameters -> log-likelihood |
|---|---|
| gradient | the gradient of the log_posterior |
| n_steps | the number of leapfrog steps |
| init_parameters | a named vector of initial parameters |
| iters | the number of iterations |
| chains | the number of chains |
| step_size | the step size of the leapfrog steps |
To run this in parallel call
future::plan(future::multiprocess()) before this function