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Comparison · Analytics
Distributions.jl vs statsmodels
A side-by-side editorial comparison of Distributions.jl and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:statisticsmaintenance
Distributions.jl vs statsmodels: at a glance
What is Distributions.jl?
Julia's distribution library grinds forward one distribution at a time
Distributions.jl ships small, frequent releases against a large and settled API surface. Recent work splits between correctness fixes to individual distributions (LogitNormal formulas, Semicircle quantiles, Truncated Chernoff), incremental fitting support such as sufficient statistics and MLE for Chi and Chisq, and infrastructure moves like more consistent error types and global sparsity tracing through constructors.
What is statsmodels?
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
Distributions.jl vs statsmodels: editorial side-by-side
Distributions.jl
2.5ANALYTICS
Julia's distribution library grinds forward one distribution at a time
◆ Current state
Distributions.jl ships small, frequent releases against a large and settled API surface. Recent work splits between correctness fixes to individual distributions (LogitNormal formulas, Semicircle quantiles, Truncated Chernoff), incremental fitting support such as sufficient statistics and MLE for Chi and Chisq, and infrastructure moves like more consistent error types and global sparsity tracing through constructors.
◆ Where it's heading
The arc is consolidation rather than expansion: dependencies are being pruned and internals made more predictable so the package composes cleanly with the rest of the Julia numerical stack. Support for sparsity tracing and looser MvNormal type aliases both point at making the library easier to drive from automatic-differentiation and optimization code.
◆ Prediction
Expect the same cadence of per-distribution fixes and fitting-method additions, with continued work on making constructors transparent to tracing and AD tooling. Nothing in these entries signals a major version or API break.
statsmodels
0.0ANALYTICS
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
◆ Current state
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
◆ Where it's heading
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
◆ Prediction
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
Alternatives to Distributions.jl and statsmodels
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 Distributions.jl or statsmodels.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
StatsBase.jl
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
iris
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
shiny
Shiny made reactive apps observable, then gave them a way to tear themselves down
See all Distributions.jl alternatives → · See all statsmodels alternatives →
Recent activity from Distributions.jl and statsmodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 16d agoDistributions.jlLogitNormal comment fix and doc typo cleanup
- 1mo agoDistributions.jlLooser MvNormal and MvNormalCanon type aliases
- 1mo agoDistributions.jlTruncated Chernoff quantile and sparsity tracing fixes
- 1mo agoDistributions.jlSparsity tracing works through distribution constructors
- 2mo agoDistributions.jlStatsFuns 2 upgrade and CI action bumps
- 3mo agoDistributions.jlSufficient statistics and MLE for Chi and Chisq
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 1y agostatsmodels0.14.5: restores importing under SciPy 1.16
- 1y agostatsmodels0.14.4: Pyodide support
- 1y agostatsmodels0.14.3: NumPy 2 environments and corrected macOS builds
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agostatsmodelsRelease 0.14.1
Frequently asked questions
What is the difference between Distributions.jl and statsmodels?
Both compete on the same themes — statistics, maintenance — within Analytics. Distributions.jl is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 Distributions.jl better than statsmodels?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Distributions.jl is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 Distributions.jl?
Top Distributions.jl alternatives in Analytics are ranked by recent ship velocity. Browse the "Distributions.jl alternatives" section above for the current picks, or visit /alternatives/distributions-jl for the full list with editorial commentary on each.
What are the best alternatives to statsmodels?
Top statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.