The Boom package provides access to the C++ BOOM library for Bayesian computation.
If you are installing Boom using install.packages on a
Linux machine (and thus compiling yourself) you will almost certainly
want to set the Ncpus argument to a large number. Windows and
Mac users can ignore this advice.
The main purpose of the Boom package is not to be used directly, but
to provide the BOOM C++ library for other packages to link against.
The Boom package provides additional utility code for C++ authors to
use when writing R packages with C++ internals. These are described
in .../inst/include/r_interface/boom_r_tools.hpp among the
package's include files.
Boom provides a collection of R functions and objects to help users
format data in the manner expected by the underlying C++ code.
Standard distributions that are commonly used as Bayesian priors can
be specified using BetaPrior, GammaPrior,
etc.
Boom provides a set of utilities helpful when writing unit tests for
Bayesian models. See CheckMcmcMatrix and
CheckMcmcVector for MCMC output, and functions like
check.probability.distribution for checking function
inputs
Boom provides a collection of useful plots (using base R graphics)
that have proven useful for summarizing MCMC output. See
PlotDynamicDistribution, PlotManyTs,
BoxplotTrue, and other code in the index with
Plot in the title.
Please see the following pacakges
bsts
CausalImpact