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Comparison · Analytics
chattr vs distributions3
A side-by-side editorial comparison of chattr and distributions3 — release velocity, themes, recent moves, and the top alternatives to consider.
chattr vs distributions3: at a glance
What is chattr?
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
What is distributions3?
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
chattr vs distributions3: editorial side-by-side
chattr
0.0ANALYTICS
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
◆ Current state
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
◆ Where it's heading
The first two releases show why that happened. Each provider brought its own error formats, token discovery and response handling, and 0.2.0 is largely a list of per-provider repairs — OpenAI error parsing, Copilot token discovery and model defaults, a new Databricks foundation model backend. Maintaining that surface scales linearly with the number of providers, and the pivot to ellmer trades it for a single dependency. The cost shows up immediately in 0.3.1, which exists solely to absorb a change in ellmer's token object.
◆ Prediction
Expect chattr's releases to now track ellmer's, as 0.3.1 already does, with the package's own work concentrating on the IDE experience rather than model connectivity. New provider support will arrive without a chattr release at all.
distributions3
6.3ANALYTICS
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
◆ Current state
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
◆ Where it's heading
Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().
◆ Prediction
With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.
Alternatives to chattr and distributions3
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either chattr or distributions3.
Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio
RStudio ships through release branches, and the notes are commit messages
dbt Core
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics
Holistics keeps fencing in the AI layer it spent the summer building.
See all chattr alternatives → · See all distributions3 alternatives →
Recent activity from chattr and distributions3
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2h agodistributions3Empirical distributions, plus score and hessian generics ⚡
- 29d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
- 10mo agodistributions3ggplot2 compatibility for the plotting functions
- 1y agochattrAdapts to ellmer's token object change
- 1y agochattrAll model integration moves to ellmer, direct backends removed ⚡
- 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
- 2y agochattrDatabricks foundation models added; per-provider error handling fixed
- 2y agochattrFirst release: LLM chat in the RStudio console and app
- 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
- 4y agodistributions3Extreme-value family, Erlang, and a plotting generic
Frequently asked questions
What is the difference between chattr and distributions3?
They serve adjacent needs but don't currently overlap on shipped themes. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is chattr better than distributions3?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to chattr?
Top chattr alternatives in Analytics are ranked by recent ship velocity. Browse the "chattr alternatives" section above for the current picks, or visit /alternatives/chattr for the full list with editorial commentary on each.
What are the best alternatives to distributions3?
Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.