qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
ardlverse vs ggmagnify
A side-by-side editorial comparison of ardlverse and ggmagnify — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ardlverse vs ggmagnify: at a glance
What is ardlverse?
An outside audit against Stata found seven errors in ardlverse's panel estimator, including regressions with no intercept.
A small R package for autoregressive distributed lag models, with only three releases on record. The first two were administrative — a CRAN version note and a Zenodo metadata update. The third, 2.0.0, is a correction release built entirely from an external audit of panel_ardl() against Stata's xtpmg, and it is the only entry here with substantive content.
What is ggmagnify?
A single-purpose ggplot2 inset tool, refining the same three arguments.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
ardlverse vs ggmagnify: editorial side-by-side
ardlverse
0.0ANALYTICS
An outside audit against Stata found seven errors in ardlverse's panel estimator, including regressions with no intercept.
◆ Current state
A small R package for autoregressive distributed lag models, with only three releases on record. The first two were administrative — a CRAN version note and a Zenodo metadata update. The third, 2.0.0, is a correction release built entirely from an external audit of panel_ardl() against Stata's xtpmg, and it is the only entry here with substantive content.
◆ Where it's heading
The package's direction is now set by verification against an established reference implementation rather than by feature work. The seven fixes bring panel_ardl() into strict alignment with the original Pesaran, Shin and Smith framework, and the most serious of them is structural: internal regressions used lm.fit(), which unlike lm() does not append an intercept, so every short-run regression across the PMG, MG and DFE estimators was forced through the origin. Design matrices now carry a column of ones and DFE reconstructs the grand-mean intercept to match standard fixed-effects output.
◆ Prediction
Expect the next releases to extend the same audit approach to the remaining estimators, since a package that has been validated against xtpmg on one function invites the same question about the rest.
ggmagnify
0.0ANALYTICS
A single-purpose ggplot2 inset tool, refining the same three arguments.
◆ Current state
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
◆ Where it's heading
Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.
◆ Prediction
Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.
Alternatives to ardlverse and ggmagnify
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 ardlverse or ggmagnify.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all ardlverse alternatives → · See all ggmagnify alternatives →
Recent activity from ardlverse and ggmagnify
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoardlverseSeven panel_ardl fixes after an audit against Stata's xtpmg
- 5mo agoardlverseZenodo metadata updated with ORCID
- 5mo agoardlverseardlverse v1.1.3
- 2y agoggmagnifyFixes inset theme override on supplied plots
- 2y agoggmagnifyAdds fill between projection lines
- 2y agoggmagnifyAdds corner radius for target and inset
Frequently asked questions
What is the difference between ardlverse and ggmagnify?
Both compete on the same themes — r-package — within Analytics. ardlverse and ggmagnify 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 ardlverse better than ggmagnify?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ardlverse and ggmagnify 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 ardlverse?
Top ardlverse alternatives in Analytics are ranked by recent ship velocity. Browse the "ardlverse alternatives" section above for the current picks, or visit /alternatives/ardlverse-r for the full list with editorial commentary on each.
What are the best alternatives to ggmagnify?
Top ggmagnify alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmagnify alternatives" section above for the current picks, or visit /alternatives/ggmagnify for the full list with editorial commentary on each.