bkmrhat
A parallel-chain helper for bkmr that has settled into pure upkeep.
A side-by-side editorial comparison of cocoon and profoc — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A forecast combination package that spun its profiler out into its own project
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
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.
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.
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.
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
The direction is toward a reusable C++ core with thin language bindings. The timing code that lived inside profoc was extracted into the standalone rcpptimer package in 1.3.2, deliberately so other R packages and Python projects could use it through cpptimer and cppytimer, and the clock header was reworked in 1.3.1 to maximise the code shared between the R and Python versions. Method work sits earlier in the history - periodic splines and penalties in 1.2.0, the penalty() function in 1.1.0 - while the recent cadence, a single release in the last sixteen months, points at a package the maintainer considers finished.
The repeated references to future Python use suggest the next significant work happens outside this package, in the shared C++ components, rather than in profoc's R surface.
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 profoc.
A parallel-chain helper for bkmr that has settled into pure upkeep.
A cancer driver prioritization package that ships rarely and mostly to stay installable
A meteorology ggplot2 extension where the netCDF reader became the main event
An isotope geolocation package still recovering from the r-spatial retirement
Functional data clustering grew from one algorithm into a comparable suite
A survival curve package spending release after release correcting its own estimates
See all cocoon alternatives → · See all profoc alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. cocoon and profoc 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cocoon and profoc 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.
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.
Top profoc alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "profoc alternatives" section above for the current picks, or visit /alternatives/profoc for the full list with editorial commentary on each.