rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of spmodel and tidytransit — release velocity, themes, recent moves, and the top alternatives to consider.
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
tidytransit reads GTFS transit feeds into tidy data frames and computes travel times using a RAPTOR implementation. Recent work splits between the reader keeping pace with the spec — locations.geojson in 1.7.0, empty strings parsed as NA in 1.8.0 — and the router gaining realism, most recently in-seat transfers. Feed specifications are now pulled from the automatically parsed GTFS reference rather than maintained by hand.
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
tidytransit reads GTFS transit feeds into tidy data frames and computes travel times using a RAPTOR implementation. Recent work splits between the reader keeping pace with the spec — locations.geojson in 1.7.0, empty strings parsed as NA in 1.8.0 — and the router gaining realism, most recently in-seat transfers. Feed specifications are now pulled from the automatically parsed GTFS reference rather than maintained by hand.
The package has settled into tracking an external standard, which is why the changelog reads as a sequence of spec conformance items rather than a roadmap. Parsing responsibility keeps shifting outward to gtfsio, and data sources have moved with the ecosystem, from the retired transitfeeds API to MobilityData. Router changes are rarer than reader changes but land in the same releases.
Further GTFS spec features are the safest expectation, with GTFS-Flex the likeliest area now that locations.geojson reading is in place.
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 spmodel or tidytransit.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all spmodel alternatives → · See all tidytransit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. spmodel and tidytransit 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. spmodel and tidytransit 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 spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.
Top tidytransit alternatives in Analytics are ranked by recent ship velocity. Browse the "tidytransit alternatives" section above for the current picks, or visit /alternatives/tidytransit-r for the full list with editorial commentary on each.