STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of rempsyc and simmer.plot — release velocity, themes, recent moves, and the top alternatives to consider.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.
simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.
The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.
simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.
This package moves when something it depends on moves. Its history is a sequence of parser fixes for new simmer trajectory formats, DiagrammeR and tidyr and dplyr version bumps, and ggplot2 workarounds. The one clear internal decision — plotting monitor output instead of the environment — was made in 2017 and completed six years later. The 2025 release fixes documentation cross-references and nothing else.
The next release most likely follows a simmer trajectory-format change or a CRAN documentation policy, matching every recent entry. There is no visible feature work in the pipeline.
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 rempsyc or simmer.plot.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all rempsyc alternatives → · See all simmer.plot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — ggplot2, r-package — within Analytics. rempsyc and simmer.plot 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. rempsyc and simmer.plot 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.
Top rempsyc alternatives in Analytics are ranked by recent ship velocity. Browse the "rempsyc alternatives" section above for the current picks, or visit /alternatives/rempsyc for the full list with editorial commentary on each.
Top simmer.plot alternatives in Analytics are ranked by recent ship velocity. Browse the "simmer.plot alternatives" section above for the current picks, or visit /alternatives/simmer-plot for the full list with editorial commentary on each.