rbi is an R
interface to libbi, a library for Bayesian inference.
It mainly contains:
bi_model
class, to manipulate libbi modelslibbi
wrapper class, to perform Bayesian using libbi inference from within R,The easiest way to install the latest stable version of rbi is via CRAN:
Alternatively, the current development version can be installed using the remotes
package
# install.packages("remotes")
library("remotes")
install_github("sbfnk/rbi")
The rbi package has only been tested on GNU/Linux and OS X, but it should mostly work everywhere R
works.
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, the easiest way is to install Homebrew, followed by (using a command shell, i.e. Terminal or similar):
On linux, follow the instructions provided with 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.
Getting startedA 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.
Using codaLibBi contains the get_traces
method which provides an interface to coda.
For higher-level methods to interact with LibBi, have a look at rbi.helpers.
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