# Install xlispstat with Homebrew Statistical data science environment based on Lisp. Version 3.52.23 via Homebrew; verified from local package data. ## Install ```sh sudo av install brew:xlispstat ``` Additional install commands: ### macOS - Homebrew (100%): ```sh brew install xlispstat ``` Evidence: local Homebrew formula metadata ## Package facts - **Package key:** brew:xlispstat - **Package manager:** Homebrew - **Package manager page:** - **Version:** 3.52.23 - **Source summary:** Statistical data science environment based on Lisp - **Homepage:** - **Upstream docs:** - **License:** HPND-sell-variant - **Source archive:** - **Generated:** 2026-07-08T07:18:31+00:00 ## Executables - xlispstat (cli) - xlispstat (alias) ## Dependencies - libx11 ## Install behavior - Post-install hook: not defined - Bottle: available on arm64_big_sur, arm64_linux, arm64_monterey, arm64_sequoia, arm64_sonoma, arm64_tahoe, arm64_ventura, big_sur, catalina, monterey, sonoma, ventura ## Freshness - Page generated: 2026-07-08 - Package-manager version: 3.52.23 - Local data: ok - Upstream repository: https://homepage.stat.uiowa.edu/~luke/xls/xlsinfo/ - info: No package-manager update timestamp was available. - info: Release/tag comparison is only available for GitHub repositories. ## Project history and usage XLISP-STAT, also called Lisp-Stat, is Luke Tierney's Lisp-based statistical computing environment for data analysis, statistical instruction, research, and dynamic graphics. It is historically important because it joined an extensible programming language, statistical modeling, and interactive graphics before R became dominant. ### Project history Tierney's Lisp-Stat information page describes the system as an extensible statistical computing environment with an emphasis on dynamic graphical methods. It is based on Lisp, extends arithmetic over lists and vectors, adds statistical and linear-algebra functions, and uses a prototype-based object system for graphics and statistical model representations. Tierney's 2005 retrospective says Lisp-Stat began in the mid-1980s as a framework for experimenting with dynamic graphics in statistics. The initial motivation was to go beyond point-cloud rotation and experiment with linked brushing, interactive scatterplot matrices, and displays integrated with a language for data manipulation. The system was documented in Tierney's 1990 Wiley book, LISP-STAT: An Object-Oriented Environment for Statistical Computing and Dynamic Graphics. By the mid-1990s, public articles described it as running across Microsoft Windows, Macintosh, and Unix/X11 systems with a relatively uniform interface. ### Adoption history XLISP-STAT found an audience in 1990s statistical computing, especially where interactive graphics and teaching mattered. Linux Journal introduced it in 1995 as a powerful, interactive, object-oriented statistical environment used for scientific work, statistical computation, matrix manipulation, hypertext illustrations, and teaching tasks. Its influence also spread through projects built on top of it. ViSta described itself as written in Lisp using XLispStat extensions and presented XLisp-Stat as open, extensible, freely available, and meant for high-level statistical programming and dynamic graphics. Usage declined as R and other environments took over statistical computing. The Journal of Statistical Software published both Tierney's retrospective and Jan de Leeuw's account of abandoning XLISP-STAT, making the package a documented case study in how research software can be influential yet lose ground to a broader ecosystem. ### How it is used Users worked interactively in a Lisp environment, using vectorized arithmetic, statistical functions, linear algebra, regression model objects, generalized linear models, and plotting facilities. Dynamic plots supported operations such as rotation, brushing, linking, mouse interaction, menus, and dialogs. For package users today, XLISP-STAT is mostly historical or archival. It remains useful for understanding statistical graphics history, old course material, and software such as Arc or ViSta that built on Lisp-Stat ideas. ### Why package nerds care XLISP-STAT matters to package nerds because it is a fossil with fingerprints everywhere: an installable scientific environment that anticipated programmable statistics, object-oriented model objects, and linked interactive graphics. It is also a reminder that scientific package history is not only a straight line toward Python and R. Lisp-Stat explored many of the same questions earlier: what should a statistical language look like, how should graphics and models be objects, and how much extensibility should users have? ### Timeline - Mid-1980s: Tierney began Lisp-Stat while experimenting with dynamic statistical graphics on Macintosh hardware. - 1990: Wiley published Tierney's LISP-STAT book documenting the object-oriented statistical environment. - 1995: Linux Journal introduced Lisp-Stat to Linux users as a cross-platform statistical computing environment. - 1998: Tierney's Lisp-Stat information page summarized the system and linked documentation, projects, bibliography, and future directions. - 2002: Journal of Statistical Software examples still used Lisp-Stat/ViSta for interactive statistical analysis extensions. - 2005: JSS published retrospective and migration-era papers discussing the past, future, and abandonment of XLISP-STAT. ### Related projects - XLISP and XLISP-PLUS are the Lisp-family substrate. ViSta and Arc are major statistical systems associated with XLISP-STAT. R is the later statistical environment most often discussed as the ecosystem that displaced it for mainstream statistical computing. ### Sources - - - - - - - - - ## Security Notes narrow executable package without higher-risk signals. - **Geiger risk:** green / low - narrow executable package without higher-risk signals ## Source Database Details - **Source Database:** Homebrew formula API - **Tap:** homebrew/core - **Full Name:** xlispstat - **Version Scheme:** 0 - **Revision:** 1 - **Bottle Stable Root URL:** - **Deprecated:** no - **Disabled:** no - **Keg Only:** no - **URL Keys:** stable ## Related links - [Terminal utility packages](https://www.automicvault.com/pkg/terminal-utilities/) - Matched terminal and command-line workflow metadata. - [Networking and protocol packages](https://www.automicvault.com/pkg/networking-protocol-tools/) - Matched network, protocol, or remote-service metadata. - [Media and graphics packages](https://www.automicvault.com/pkg/media-graphics-tools/) - Matched media, image, audio, video, or graphics metadata. - [Database and data packages](https://www.automicvault.com/pkg/database-data-tools/) - Matched database, SQL, migration, or data-store metadata. - [healpix](https://www.automicvault.com/pkg/brew/healpix/) - Shares av.db curated category or tags: cli, data-analysis, science, scientific-computing. - [root](https://www.automicvault.com/pkg/brew/root/) - Shares av.db curated category or tags: cli, data-analysis, science, scientific-computing. - [ent](https://www.automicvault.com/pkg/brew/ent/) - Shares av.db curated category or tags: cli, science, statistics. - [gnuastro](https://www.automicvault.com/pkg/brew/gnuastro/) - Shares av.db curated category or tags: cli, data-analysis, science. - [qsoas](https://www.automicvault.com/pkg/brew/qsoas/) - Shares av.db curated category or tags: cli, data-analysis, science. - [snakemake](https://www.automicvault.com/pkg/brew/snakemake/) - Shares av.db curated category or tags: cli, data-analysis, science. - [gwyddion](https://www.automicvault.com/pkg/brew/gwyddion/) - Shares av.db curated category or tags: cli, data-analysis, science. - [jags](https://www.automicvault.com/pkg/brew/jags/) - Shares av.db curated category or tags: cli, science, statistics. ## Combined YAML source View the package source record on GitHub. [combined/xlispstat.yml](https://github.com/automic-vault/db/blob/main/combined/xlispstat.yml) ## Sources - Nucleus package database - Geiger risk classifier - package-page enrichment - curated package history - package version freshness - av.db category and tag curation - package relationship graph - cross-ecosystem install command graph