Man pages for nickseedorff/pmmhLong
Pseudo-marginal Metroplis Hastings for Efficient Multivariate Longitudinal Poisson Regression
| calc_gradient | Calculate the gradient |
| calc_hessian | Caluate the hessian |
| diag_each_chain | Attain diagnostics for each chain |
| evaluate_pmmh | Build a dataset for easy testing |
| gen_data | Build a dataset for easy testing |
| gen_data_mats | Build data matrices for ingestion by gen_pmll_estim() |
| get_pmll_estim | Get estimates of the marginal likelihood values |
| get_posterior_modes | Get posterior modes using laplace approximation |
| get_post_estim | Get values for MH accept step |
| maxim_test | Get values for MH accept step |
| pmmh | Get values for MH accept step |
| pmmh_diags | Attain diagnostics for all chaings |
| pmmh_geweke | Get values for MH accept step |
| pmmh_hist | Get values for MH accept step |
| pmmh_single_chain | Run pmmh for a single chain |
| pmmh_trace | Get values for MH accept step |
| prepare_data | Prepare data for loop within pmmh |
| prepare_storage | Prepare storage for results |
| single_step | Take a single step in the newton raphson algorithm |
