Bayesian inference for state-space models with R
It mainly contains:
- various functions to retrieve and process the results from libbi (which are in NetCDF format)
bi_modelclass, to manipulate libbi models
libbiwrapper class, to perform Bayesian using libbi inference from within R,
RBi requires R (>= 2.12.1) as well as the packages:
The easiest way to install the latest stable version of RBi is via CRAN. The package is called
rbi (all lower case):
Alternatively, the current development version can be installed using the
# install.packages("devtools") library('devtools') install_github("libbi/rbi")
The RBi package has only been tested on GNU/Linux and OS X, but it should mostly work everywhere
If you want to use RBi as a wrapper to LibBi then you need a working version of LibBi. To install LibBi on a Mac or Unix, the easiest way is to install Homebrew (on OS X) or Linuxbrew (on linux), followed by (using a command shell, i.e. Terminal or similar):
brew install libbi
The path to
libbi script can be passed as an argument to RBi, otherwise the package tries to find it automatically using the
which linux/unix command.
If you just want to process the output from LibBi, then you do not need to have LibBi installed.
A good starting point is to look at the included demos:
demo(PZ_generate_dataset) ## generating a data set from a model demo(PZ_PMMH) ## particle Markov-chain Metropolis-Hastings demo(PZ_SMC2) ## SMC^2 demo(PZ_filtering) ## filtering
For further information, have a look at the introductory vignette from the link from the rbi CRAN package.
LibBi contains the
get_traces method which provides an interface to coda.