LibBi might nominally stand for Library for Bayesian inference, although is not meant to be an abbreviation as such. Development of the software began in 2009, with a working title of just Bi (for Bayesian inference), which, at the time, was sufficiently generic for anything we might want to put in it. Lib was added closer to public release, when something more unique was required.
Whichever you prefer, and for as long as you like, until you settle on "Libby".
Development of LibBi began in 2009 at CSIRO. The aim of the initial project was to develop appropriate models and methodology for quantifying uncertainty in marine biogeochemical models. Recognising potential interest in the broader scientific community, the software was released under an open source licence in June 2013 and has since been used in several other problem domains.
The main developer is Lawrence Murray. Sebastian Funk has made significant contributions, especially to the RBi interface for R, and Homebrew packaging.
LibBi is licensed under the CSIRO Open Source Software License (GPL). This is the full text of the GPL version 2 with some additional provisions.
Please cite the following paper:
L. M. Murray, Bayesian state-space modelling on high-performance hardware using LibBi, 2013. [arXiv]
You can! But that may not be your best choice, depending on the problem you have at hand. LibBi differs from these packages in two ways:
The first point is reflected in the methods for inference that LibBi has
available. Its staple methods are from the family of sequential Monte Carlo
(SMC), not Gibbs (as in BUGS and JAGS) or Hamiltonian Monte Carlo (as in
Stan). LibBi can be used for non-SSMs by omitting the transition and
initial blocks in a model specification, but its machinery for such models
is rudimentary at this stage. The potential is there to develop in such a
direction in future, however.
We are not aware of other software packages in this space that have the same high performance computing orientation as LibBi.