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Comparison · Infra & APIs

cocoon vs estimatr

A side-by-side editorial comparison of cocoon and estimatr — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

cocoon vs estimatr: at a glance

Featurecocoonestimatr
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, statistics, reporting, maintenancecausal-inference, experiments, robust-standard-errors, econometrics
Last editorial update1h ago48m ago
WebsiteVisit →Visit →

What is cocoon?

A statistics-formatting helper in maintenance mode, tracking R-devel one fix at a time

cocoon formats statistical output for manuscripts, converting model and test objects into publication-ready strings. Its surface settled early: format_stats() is a generic that dispatches on object class, introduced in 0.1.0 to supersede the earlier format_corr() and format_ttest(), and extended in 0.2.0 to cover aov, lm, glm and the lme4 and lmerTest mixed-model families. The two releases since have been single-issue compatibility fixes against changes to wilcox.test() in R-devel.

Read the full cocoon trajectory →

What is estimatr?

Fast design-based estimators for experiments, coasting on CRAN patches.

estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.

Read the full estimatr trajectory →

cocoon vs estimatr: editorial side-by-side

C
cocoon
INFRA · APIS
0.0

A statistics-formatting helper in maintenance mode, tracking R-devel one fix at a time

◆ Current state

cocoon formats statistical output for manuscripts, converting model and test objects into publication-ready strings. Its surface settled early: format_stats() is a generic that dispatches on object class, introduced in 0.1.0 to supersede the earlier format_corr() and format_ttest(), and extended in 0.2.0 to cover aov, lm, glm and the lme4 and lmerTest mixed-model families. The two releases since have been single-issue compatibility fixes against changes to wilcox.test() in R-devel.

◆ Where it's heading

The package reached feature completeness for its stated job quickly and has been in maintenance since early 2025. Both 0.2.1 and 0.3.1 address the same upstream moving part - how wilcox.test() computes exact versus asymptotic distributions in development versions of R - which is the shape of a package whose own code is stable and whose risk lives entirely in what it wraps. Nothing in the recent entries points at new statistical object types.

◆ Prediction

Further releases are likely to stay reactive, triggered by R-devel or dependency changes rather than by new formatting methods, unless a specific model class is requested.

E
estimatr
INFRA · APIS
0.0

Fast design-based estimators for experiments, coasting on CRAN patches.

◆ Current state

estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.

◆ Where it's heading

Direction cannot be read from this feed. The release notes are unedited merge-commit messages, so the only signal is cadence — roughly annual, each release framed as a CRAN patch rather than as feature work. That pattern is consistent with a package whose estimators are considered finished and which now moves only when CRAN policy requires it.

◆ Prediction

On the evidence here the next release is another CRAN compliance patch, but the notes are too thin to support a confident read of what the maintainers are actually working on.

Alternatives to cocoon and estimatr

Other Infra & APIs 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 cocoon or estimatr.

See all cocoon alternatives → · See all estimatr alternatives →

Recent activity from cocoon and estimatr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agococoonTest fix for wilcox.test changes in R-devel
  2. 11mo agococoonSuppress an R-devel warning in htest testing
  3. 1y agoestimatrCRAN version 1.0.4
  4. 1y agococoonformat_stats gains regression and mixed-model methods
  5. 1y agococoonformat_stats generic supersedes the per-test formatters
  6. 1y agococoonPre-release tag of the 0.1.0 contents
  7. 2y agoestimatrCRAN version 1.0.2
  8. 3y agoestimatrCRAN version 1.0.0

Frequently asked questions

What is the difference between cocoon and estimatr?

Both compete on the same themes — r-package — within Infra & APIs. cocoon and estimatr 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 cocoon better than estimatr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cocoon and estimatr 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to cocoon?

Top cocoon alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "cocoon alternatives" section above for the current picks, or visit /alternatives/cocoon for the full list with editorial commentary on each.

What are the best alternatives to estimatr?

Top estimatr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "estimatr alternatives" section above for the current picks, or visit /alternatives/estimatr for the full list with editorial commentary on each.