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