simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of gghighlight and nmar — release velocity, themes, recent moves, and the top alternatives to consider.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().
NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().
Two threads run through the history. One is a slow deprecation, from soft-deprecating the geom-specific functions at 0.1.0, to defunct at 0.3.0, to removed at 0.5.0 — a five-year removal cycle. The other is compatibility work: purrr 1.0.0, dplyr's across() deprecation, ggplot2 3.4.0, then 4.0. Genuine feature additions are rare and small, with line_label_type at 0.4.0 the last one. Note that 0.3.2's notes restate 0.3.1's n() item, so adjacent tags here overlap rather than each describing distinct work.
The next release most likely absorbs further ggplot2 4.x changes, given that is what triggered the last three. Nothing in the entries points to a new highlighting capability.
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
The package is positioning itself as the general interface to nonignorable-nonresponse estimation rather than a reference implementation of one paper — shared architecture across engines, one formula API, and integration with the survey package so weights and stratification come for free. The follow-up releases suggest the next constraint is compute: bootstrap variance estimation is the expensive part, and it now dispatches to future.apply when a parallel plan exists.
Expect further engines under the same nmar() interface or wider bootstrap support, since the architecture was explicitly refactored to share structure across estimators.
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 gghighlight or nmar.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all gghighlight alternatives → · See all nmar alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. gghighlight and nmar 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. gghighlight and nmar 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 gghighlight alternatives in Analytics are ranked by recent ship velocity. Browse the "gghighlight alternatives" section above for the current picks, or visit /alternatives/gghighlight for the full list with editorial commentary on each.
Top nmar alternatives in Analytics are ranked by recent ship velocity. Browse the "nmar alternatives" section above for the current picks, or visit /alternatives/nmar for the full list with editorial commentary on each.