title: MCMC_CLIB-an advanced MCMC sampling package for ODE models.
abstract: CONCLUSIONS
  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.
  
  
  METHODS
  The source code and binary files are freely available for download at http://a-kramer.github.io/mcmc_clib/. This also includes example files and data. A detailed documentation, an example model and user manual are provided with the software.
  
  
  BACKGROUND
  andrei.kramer@ist.uni-stuttgart.de.
authors.affiliation: Institute for Systems Theory and Automatic Control, University of Stuttgart, 70569 Stuttgart, Germany, Department of Statistical Science, University College, London WC1E 6BT, UK and Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Andrei
authors.initials: A
authors.lastname: Kramer
authors.affiliation: Institute for Systems Theory and Automatic Control, University of Stuttgart, 70569 Stuttgart, Germany, Department of Statistical Science, University College, London WC1E 6BT, UK and Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Vassilios
authors.initials: V
authors.lastname: Stathopoulos
authors.affiliation: Institute for Systems Theory and Automatic Control, University of Stuttgart, 70569 Stuttgart, Germany, Department of Statistical Science, University College, London WC1E 6BT, UK and Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Mark
authors.initials: M
authors.lastname: Girolami
authors.affiliation: Institute for Systems Theory and Automatic Control, University of Stuttgart, 70569 Stuttgart, Germany, Department of Statistical Science, University College, London WC1E 6BT, UK and Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Nicole
authors.initials: N
authors.lastname: Radde
mesh_terms: D000465:Algorithms; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D012984:Software