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 singlercapture — 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.
singleRcapture reached 1.0.0 with no release notes at all — the arc has to be read backwards.
A package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
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.
A package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
The direction visible in 0.2.x is outward: refactoring for maintainability, extending to models fitted elsewhere via a subclass, adding a JSS-paper vignette, and pushing coverage towards 90%. That is a package preparing to be cited and extended rather than one still finding its methods. The 1.0.0 tag presumably marks the end of that stabilisation, but the entry itself gives no evidence either way.
Not readable from this feed — the 1.0.0 notes are empty, so whether the major version marks an API freeze or a breaking change cannot be determined from the entries shown.
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 singlercapture.
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 singlercapture alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. rempsyc and singlercapture 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 singlercapture 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 singlercapture alternatives in Analytics are ranked by recent ship velocity. Browse the "singlercapture alternatives" section above for the current picks, or visit /alternatives/singlercapture for the full list with editorial commentary on each.