We’ve released the newest version of NIMBLE on CRAN and on our website.

Version 0.6-11 has important new features, notably support for Bayesian nonparametric mixture modeling, and more are on the way in the next few months.

New features include:

• support for Bayesian nonparametric mixture modeling using Dirichlet process mixtures, with specialized MCMC samplers automatically assigned in NIMBLE’s default MCMC (See Chapter 10 of the manual for details);
• additional resampling methods available with the auxiliary and bootstrap particle filters;
• user-defined filtering algorithms can be used with NIMBLE’s particle MCMC samplers;
• MCMC thinning intervals can be modified at MCMC run-time;
• both runMCMC() and nimbleMCMC() now drop burn-in samples before thinning, making their behavior consistent with each other;
• increased functionality for the ‘setSeed’ argument in nimbleMCMC() and runMCMC();
• new functionality for specifying the order in which sampler functions are executed in an MCMC; and
• invalid dynamic indexes now result in a warning and NaN values but do not cause execution to error out, allowing MCMC sampling to continue.

Please see the NEWS file in the installed package for more details