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The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of ardlverse and gtfstools — release velocity, themes, recent moves, and the top alternatives to consider.
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.
gtfstools stopped guarding its own object model and started accepting everyone else's.
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
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.
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.
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.
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
The package built out a wide function surface first — filters, geometry conversion, speed and duration calculations — then turned outward. Delegating validation to MobilityData's validator and accepting other packages' objects both trade self-sufficiency for a position inside the wider GTFS ecosystem. Deprecations are handled slowly, with old behaviour left as the default for a release or more.
Expect continued validator version tracking and further completion of the deprecation cycle around filter_by_stop_id()'s full_trips behaviour.
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 gtfstools.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all ardlverse alternatives → · See all gtfstools alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. ardlverse and gtfstools 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. ardlverse and gtfstools 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 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.
Top gtfstools alternatives in Analytics are ranked by recent ship velocity. Browse the "gtfstools alternatives" section above for the current picks, or visit /alternatives/gtfstools-r for the full list with editorial commentary on each.