# Installer libbi avec Homebrew

Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de libbi pour les workflows d'agents IA.

## installation

```sh
sudo av install brew:libbi
```

Commandes d'installation supplémentaires:

### macOS

- Homebrew (100%):

```sh
brew install libbi
```

  Preuve: local Homebrew formula metadata

## Faits du paquet

- **Clé du paquet:** brew:libbi
- **Gestionnaire de paquets:** Homebrew
- **Version:** 1.4.5
- **Résumé source:** Bayesian state-space modelling on parallel computer hardware
- **Page d'accueil:** <https://libbi.org/>
- **Dépôt:** <https://github.com/lawmurray/LibBi>
- **Généré:** 2026-08-03T19:37:03+00:00

## exécutables

- bi (alias)
- libbi (alias)

## Comportement d'installation

- Bouteille: non disponible

## Version et fraîcheur

- page générée: 2026-08-03
- version du gestionnaire: 1.4.5
## Historique du projet et usages

LibBi is Lawrence M. Murray's package for Bayesian state-space modelling and inference on high-performance hardware. It combines a C++ template library with a Perl parser and compiler for a domain-specific modelling language.

### Historique du projet

LibBi was publicly announced on 2013-06-07, alongside Murray's 2013 paper on Bayesian state-space modelling on high-performance hardware. The paper presents LibBi as software that parses a model language, optimizes it, generates C++ code, compiles it, and runs inference methods on CPU, GPU, and distributed-memory platforms.

The project site frames LibBi around sequential Monte Carlo methods, including particle filtering, PMCMC, SMC^2, the extended Kalman filter, and parameter optimization routines. Its design reflects a scientific-computing period when CUDA, OpenMP, MPI, NetCDF, and HDF5 were expected to be stitched together by domain-specific tooling.

### Historique d'adoption

LibBi found a niche in statistical and scientific modelling rather than general-purpose application development. The project site records an RBi package announcement on 2016-10-19 for using LibBi from R, and a 2016-11-14 post announcing Homebrew and Linuxbrew installation for `libbi`.

### Modes d'utilisation

Users write state-space models in LibBi's modelling language, then run the `libbi` or `bi` tools to perform inference and process NetCDF/HDF5-backed input and output. The package is aimed at researchers who want particle methods and hardware parallelism without hand-writing the full generated C++ implementation.

### Pourquoi les passionnés de paquets s'y intéressent

LibBi is a good example of a package-manager formula preserving a research software stack: C++, Perl, CUDA-era assumptions, NetCDF/HDF5-style data, and a custom DSL all bundled as a command-line tool. It is niche, but interesting because the package is the executable surface of an academic modelling system.

### Chronologie

- 2013: Initial release of LibBi is announced on 2013-06-07.
- 2013: Introductory LibBi paper is listed by the project for citation.
- 2016: RBi interface for R is announced on 2016-10-19.
- 2016: Homebrew and Linuxbrew installation is announced on 2016-11-14.
- 2019: Project news lists LibBi 1.4.5 on 2019-07-08.

### Related projects

- RBi, R, MATLAB, GNU Octave, Julia, CUDA, OpenMP, MPI, NetCDF, HDF5, and sequential Monte Carlo research code are the most relevant neighbors.

### Sources

- <https://github.com/lawmurray/LibBi>
- <https://libbi.org/>
- <https://libbi.org/2013/06/07/LibBi-Released>
- <https://libbi.org/2016/10/19/LibBi-package-for-R>
- <https://libbi.org/2016/11/14/Easily-install-LibBi-from-Homebrew>
- <https://libbi.org/documentation>
- <https://libbi.org/getting-started>
- <https://libbi.org/papers>


## Notes de sécurité

library-like package without higher-risk signals.

- **Risque Geiger:** vert / faible
- library-like package without higher-risk signals


## Combined YAML source

View the package source record on GitHub. [combined/libbi.yml](https://github.com/mxcl/pkgdb/blob/main/combined/libbi.yml)


## Sources

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- cross-ecosystem install command graph