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ggtrace vs nmar

A side-by-side editorial comparison of ggtrace and nmar — release velocity, themes, recent moves, and the top alternatives to consider.

ggtrace vs nmar: at a glance

Featureggtracenmar
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, debugging, ggproto, developer-toolingsurvey statistics, nonresponse, empirical likelihood, bootstrap
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is ggtrace?

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.

Read the full ggtrace trajectory →

What is nmar?

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.

Read the full nmar trajectory →

ggtrace vs nmar: editorial side-by-side

G
ggtrace
ANALYTICS
0.0

A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

N
nmar
ANALYTICS
0.0

NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

Expect further engines under the same nmar() interface or wider bootstrap support, since the architecture was explicitly refactored to share structure across estimators.

Alternatives to ggtrace and nmar

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.

See all ggtrace alternatives → · See all nmar alternatives →

Recent activity from ggtrace and nmar

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 6mo agonmarBootstrap backend now parallel-aware and configurable
  2. 7mo agonmarCRAN submission fixes and DOI references
  3. 8mo agonmarNMAR 0.1.0
  4. 1y agoggtraceBrace-less one-liner methods traced gracefully
  5. 1y agoggtraceget_method_inheritance() fixed for class instances
  6. 1y agoggtraceWorkflow functions recognise one-liner ggproto methods
  7. 1y agoggtraceEager layer_is(), clearer method-mismatch errors, consistent tracedump names
  8. 1y agoggtracetrace_steps = "all" added; double-evaluation side effects fixed
  9. 1y agoggtracelayer_is() targets by_layer() downstream directly

Frequently asked questions

What is the difference between ggtrace and nmar?

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.

Is ggtrace better than nmar?

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.

What are the best alternatives to ggtrace?

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.

What are the best alternatives to nmar?

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.