mcmc_clib–an advanced MCMC sampling package for ode models

We present a new C implementation of an advanced Markov chain Monte Carlo (MCMC) method for the sampling of ordinary differential equation (ode) model parameters. The software mcmc_clib uses the simplified manifold Metropolis-adjusted Langevin algorithm (SMMALA), which is locally adaptive; it uses the parameter manifold’s geometry (the Fisher information) to make efficient moves. This adaptation does not diminish with MC length, which is highly advantageous compared with adaptive Metropolis techniques when the parameters have large correlations and/or posteriors substantially differ from multivariate Gaussians. The software is standalone (not a toolbox), though dependencies include the GNU scientific library and sundials libraries for ode integration and sensitivity analysis.