Author Archives: Chris Paciorek

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 0.5 released!

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We’ve just released the next major version of NIMBLE.

Changes include

  • more efficient computations for conjugate sampling,
  • additional automated checking of BUGS syntax to improve NIMBLE’s warning/error messages,
  • new API functionality to allow the use of syntax such as model$calculate(), etc. (syntax such as calculate(model) still works),
  • new API functionality for MCMC sampler specification,
  • improvements in speed and memory use in building models,
  • addition of forwardsolve, backsolve, and solve to the NIMBLE DSL, and
  • a variety of other items.

More details in the NEWS file that accompanies the package.

We anticipate being on CRAN in coming weeks and a next release soon that will include a full suite of sequential Monte Carlo (i.e., particle filtering) algorithms.

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.