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Comparison · Analytics
distributions3 vs vim
A side-by-side editorial comparison of distributions3 and vim — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
distributions3 vs vim: at a glance
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.
What is vim?
Six dormant years end with a correctness audit across VIM's entire imputation surface
VIM handles visualization and imputation of missing values in R, with kNN, hot-deck, iterative robust model-based imputation and matching-based methods. Development effectively stopped after 6.0.0 in 2020. Version 7.2.0 arrives in July 2026 as an explicitly framed correctness milestone: MI-properness warnings, ordered-factor preservation, a keep_all_columns option, list returns from irmi(mi>1), repairs to imputeRobust and imputeRobustChain, cellwise IRWLS and initial-weight fixes, and kNN and gowerD mixed-scaling corrections with a weightDist guard.
distributions3 vs vim: editorial side-by-side
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.
vim
0.0ANALYTICS
Six dormant years end with a correctness audit across VIM's entire imputation surface
◆ Current state
VIM handles visualization and imputation of missing values in R, with kNN, hot-deck, iterative robust model-based imputation and matching-based methods. Development effectively stopped after 6.0.0 in 2020. Version 7.2.0 arrives in July 2026 as an explicitly framed correctness milestone: MI-properness warnings, ordered-factor preservation, a keep_all_columns option, list returns from irmi(mi>1), repairs to imputeRobust and imputeRobustChain, cellwise IRWLS and initial-weight fixes, and kNN and gowerD mixed-scaling corrections with a weightDist guard.
◆ Where it's heading
The release notes describe an audit — Wave 1 plus tail — rather than a feature cycle, and the fixes cluster around statistical validity: whether multiple imputation is proper, whether factor ordering survives, whether distance scaling across mixed variable types is right. Those are the properties users cannot easily verify themselves, so a package correcting them after six years is implicitly restating what its earlier output was worth. The notes also name a forthcoming R Journal paper under the name vimpute, which points at a successor or companion identity.
◆ Prediction
The entries call this a stable reference point for a paper and refer to Wave 1, so a further audit wave is the most likely next release; the vimpute naming is worth watching but the entries do not say what it is.
Alternatives to distributions3 and vim
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 distributions3 or vim.
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.
Dovetail
Dovetail spent July opening doors to other tools and August making its own rooms easier to enter.
See all distributions3 alternatives → · See all vim alternatives →
Recent activity from distributions3 and vim
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2h agodistributions3Empirical distributions, plus score and hessian generics ⚡
- 28d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
- 1mo agovimCorrectness audit fixes MI-properness, factor order and distance scaling
- 10mo agodistributions3ggplot2 compatibility for the plotting functions
- 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
- 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
- 4y agodistributions3Extreme-value family, Erlang, and a plotting generic
- 6y agovimAdds ranger-based imputation, drops survey and GUI support
- 6y agovimAdds nine example datasets and splits help pages
- 6y agovimAdds matchImpute() and random-forest augmented kNN
- 6y agovimOrdered factor support and ordinal regression in irmi()
- 6y agovimBug fixes for kNN, hotdeck and irmi input handling
Frequently asked questions
What is the difference between distributions3 and vim?
Both compete on the same themes — r-package — within Analytics. 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 distributions3 better than vim?
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 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.
What are the best alternatives to vim?
Top vim alternatives in Analytics are ranked by recent ship velocity. Browse the "vim alternatives" section above for the current picks, or visit /alternatives/vim for the full list with editorial commentary on each.