Category Archives: Releases

Version 0.6-2 released!

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Version 0.6-2 is a minor release with a variety of useful functionality for users.

Changes as of Version 0.6-2 include:

  • user-defined distributions can be used in BUGS code without needing to call the registerDistributions() function (unless one wants to specify alternative parameterizations, distribution range or that the distribution is discrete),
  • users can now specify the use of conjugate (Gibbs) samplers for nodes in a model,
  • NIMBLE will now check the run code of nimbleFunctions for functions (in particular R functions) that are not part of the DSL and will not compile,
  • added getBound() functionality to find the lower and upper bounds of a node either from R or in DSL code,
  • added functionality to get distributional information about a node in a model or information about a distribution based on the name of the density function; these may be useful in setup code for algorithms,
  • multinomial and categorical distributions now allow ‘probs’ arguments that do not sum to one (these will be internally normalized) and
  • a variety of bug fixes.

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

Version 0.5-1 of NIMBLE released!

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Version 0.5-1 is officially a minor release, but it actually has quite a bit in it, in particular the addition/improvement of a number of our algorithms. In addition there are some more improvements in our speed in building and compiling models and algorithms.

Changes as of Version 0.5-1 include:

  • the addition of a variety of sequential Monte Carlo (aka particle filtering) algorithms, including particle MCMC samplers for use within an MCMC,
  • a greatly improved MCEM algorithm with an automated convergence and stopping criterion,
  • new syntax for declaring multivariate variables in the NIMBLE DSL, namely numeric(), integer(), matrix(), and array(), with declare() now deprecated,
  • addition of the multivariate-t distribution for use in BUGS and DSL code,
  • a new binary MCMC sampler for discrete 0/1 nodes,
  • addition of functionality to our random walk sampler to allow sampling on the log scale and use of reflection,
  • more flexible use of forwardsolve(), backsolve(), and solve(), including use in BUGS code, and
  • a variety of other items.

Please see the NEWS file in the source package.

Version 0.4-1 released!

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We’ve just released version 0.4-1, a minor release that fixes some logistical issues and adds a bit of functionality to our MCMC engine.

Changes as of Version 0.4-1 include:

  • added an elliptical slice sampler to the MCMC engine,
  • fixed bug preventing use of nimbleFunctions in packages depending on NIMBLE, and
  • reduced C++ compiler warnings on Windows during use of compileNimble.

Version 0.4 released!

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In late July we released a major new version of NIMBLE, 0.4.  Ok, that’s still a low version number, indicating we have a lot we still want to build and improve, but this version can do a lot and is a huge step forward from 0.3.  Almost everything runs faster, from model building to model and nimbleFunction compiling to compiled execution.  New features include the ability to write your own functions and distributions for BUGS (as nimbleFunctions, of course) and an algorithm that automatically adapts blocks of correlated parameters for efficient joint sampling in MCMC.  Read NEWS (link here) for more details.  The same information is also on github (here).