JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of fastpos and tidyplots — release velocity, themes, recent moves, and the top alternatives to consider.
Dormant three years, then a two-line release nobody using it would notice
fastpos finds the critical point of stability for a Pearson correlation, a simulation problem whose C++ implementation is the entire reason the package exists. Its substantive work concluded in 2022 with 0.5.0, the release prepared during R Journal review, which renamed the precision parameters, moved multicore work to pbapply and let users set corridor limits directly. After three years of silence, 0.6.0 removes an internal restriction to cpp11 and changes index_pop to an integer.
tidyplots keeps rebuilding its own foundations rather than layering around them.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
fastpos finds the critical point of stability for a Pearson correlation, a simulation problem whose C++ implementation is the entire reason the package exists. Its substantive work concluded in 2022 with 0.5.0, the release prepared during R Journal review, which renamed the precision parameters, moved multicore work to pbapply and let users set corridor limits directly. After three years of silence, 0.6.0 removes an internal restriction to cpp11 and changes index_pop to an integer.
This is a finished piece of research software in low-effort upkeep. The changelog's centre of gravity is the R Journal review process, and once that concluded the package stopped changing. The single release since is toolchain work of the kind that keeps a package compiling rather than anything a user would see.
Expect nothing beyond occasional compilation or CRAN-check fixes unless the accompanying paper draws requests for other correlation types or resampling schemes.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
The package is converging on ggplot2 rather than abstracting away from it: split_plot() now uses facet_wrap and facet_grid, as_tidyplot() was hard-deprecated on the grounds that converting a ggplot was never a good idea, and releases are timed against upstream ggplot2 versions. The other constant is the statistics surface, which has grown from basic error bars to paired and selected comparisons. Breaking changes are announced plainly and frequently, consistent with a package using 0.x to fix its shape before committing.
The patchwork removal is described as something that will eventually break dependent code, so the near-term work is likely completing that migration and settling the split_plot() parameters introduced alongside it. A 1.0 would signal the breaking-change cadence is ending, and nothing here indicates that yet.
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 fastpos or tidyplots.
Recurrent-event modelling settles, with mean_no() promoted to stable.
Nonparametric change point detection swaps p-values for importance scores.
A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.
Wavelet trend estimation tightens the defaults it shipped with.
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
mice can finally predict, not just estimate, from multiply imputed data.
See all fastpos alternatives → · See all tidyplots alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. fastpos and tidyplots 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. fastpos and tidyplots 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 fastpos alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "fastpos alternatives" section above for the current picks, or visit /alternatives/fastpos for the full list with editorial commentary on each.
Top tidyplots alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyplots alternatives" section above for the current picks, or visit /alternatives/tidyplots for the full list with editorial commentary on each.