simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of ggtrace and nmar — release velocity, themes, recent moves, and the top alternatives to consider.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
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.
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
The package matured from raw tracing primitives into named workflows: 0.6.0 added the sublayer snapshot functions and error-context helpers, 0.7.x has been sanding down how reliably those workflows find and evaluate a method. Three consecutive releases in May 2025, two of them minutes apart, all address the same class of failure — one-liner ggproto methods without braces, and inheritance resolution on instances rather than subclasses. That pattern says the remaining bugs are in method introspection, not in the tracing machinery itself.
Expect continued fixes to method resolution as ggplot2's ggproto definitions vary, and realignment work when ggplot2 4.x changes internals this package deliberately reaches into. The entries do not signal new workflow functions.
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 ggtrace 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 ggtrace 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. ggtrace 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. ggtrace 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 ggtrace alternatives in Analytics are ranked by recent ship velocity. Browse the "ggtrace alternatives" section above for the current picks, or visit /alternatives/ggtrace 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.