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Comparison · Analytics
cmdstanpy vs statsmodels
A side-by-side editorial comparison of cmdstanpy and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:python
cmdstanpy vs statsmodels: at a glance
What is cmdstanpy?
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
CmdStanPy is at v1.3.0, which added a diagnose method on CmdStanModel, sampler timing information, create_inits() across the stanfit classes, and much faster MCMC CSV parsing. Every release in this window opens with the same notice: the next non-bugfix release will be 2.0 and will remove existing deprecations. In line with that, 1.3.0 drops Python 3.8 and renames the metric argument to inv_metric.
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.
cmdstanpy vs statsmodels: editorial side-by-side
cmdstanpy
0.0ANALYTICS
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
◆ Current state
CmdStanPy is at v1.3.0, which added a diagnose method on CmdStanModel, sampler timing information, create_inits() across the stanfit classes, and much faster MCMC CSV parsing. Every release in this window opens with the same notice: the next non-bugfix release will be 2.0 and will remove existing deprecations. In line with that, 1.3.0 drops Python 3.8 and renames the metric argument to inv_metric.
◆ Where it's heading
The package tracks upstream Stan and prepares for its own break. New inference methods arrive as Stan ships them — Laplace with Stan 2.32, Pathfinder with 2.33 — while the interface work is mostly deprecation staging and CSV input-output performance. The repeated 2.0 warning across two years of releases suggests the cut has been deferred more than once.
◆ Prediction
The notice at the top of every release points to 2.0 as the next non-bugfix version, removing the deprecations staged here including the metric argument.
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 cmdstanpy 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 cmdstanpy or statsmodels.
modeltime
modeltime built conformal intervals in, then went quiet on features.
performance
performance keeps adding ways to check a model you have already fitted.
dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
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.
See all cmdstanpy alternatives → · See all statsmodels alternatives →
Recent activity from cmdstanpy and statsmodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 9mo agocmdstanpydiagnose method, sampler timings and faster CSV parsing
- 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 agocmdstanpyFixes from_csv() for CmdStan 2.35 and later
- 2y agocmdstanpyCmdStan 2.35 test fixes and multi-chain profile output
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agocmdstanpypyproject.toml build and pathfinder() argument fixes
- 2y agocmdstanpyNew Pathfinder arguments and warmup without adaptation
- 2y agostatsmodelsRelease 0.14.1
- 2y agocmdstanpyLaplace method and Pathfinder exposed from upstream Stan
Frequently asked questions
What is the difference between cmdstanpy and statsmodels?
Both compete on the same themes — python — within Analytics. cmdstanpy and statsmodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is cmdstanpy better than statsmodels?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cmdstanpy and statsmodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to cmdstanpy?
Top cmdstanpy alternatives in Analytics are ranked by recent ship velocity. Browse the "cmdstanpy alternatives" section above for the current picks, or visit /alternatives/cmdstanpy 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.