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The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of gtfstools and modeltime.resample — release velocity, themes, recent moves, and the top alternatives to consider.
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.
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
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.
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
Every entry here is compatibility work against something upstream — hardhat 1.0.0, workflows regression mode, then tune 2.0.0 twice. The 0.3.0 notes show a second concern emerging alongside it: making failures legible, with .notes on failed fits, actionable errors from unnest_modeltime_resamples(), and fallback logic when prediction columns go missing across versions. Reproducibility gets the same treatment through explicit seeding.
Expect the next release to track the next tidymodels breaking change, with any new work continuing on error reporting rather than resampling strategies.
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 gtfstools or modeltime.resample.
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 gtfstools alternatives → · See all modeltime.resample alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. gtfstools and modeltime.resample 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. gtfstools and modeltime.resample 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 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.
Top modeltime.resample alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime.resample alternatives" section above for the current picks, or visit /alternatives/modeltime-resample for the full list with editorial commentary on each.