rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
collapse vs spmodel
A side-by-side editorial comparison of collapse and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
collapse vs spmodel: at a glance
What is collapse?
collapse got a JSS paper and a 7x fmean speedup in the same release.
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
What is spmodel?
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.
collapse vs spmodel: editorial side-by-side
collapse
0.0ANALYTICS
collapse got a JSS paper and a 7x fmean speedup in the same release.
◆ Current state
collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().
◆ Where it's heading
The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.
◆ Prediction
Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to collapse and spmodel
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 collapse or spmodel.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all collapse alternatives → · See all spmodel alternatives →
Recent activity from collapse and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 7mo agocollapseNegative zero now hashes equal to zero across the package
- 8mo agocollapsecollap() no longer double-aggregates external weights
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 9mo agocollapseCustom unlist() preserves attributes
- 0y agocollapseAssorted bug fixes
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
Frequently asked questions
What is the difference between collapse and spmodel?
Both compete on the same themes — r-package — within Analytics. collapse and spmodel 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 collapse better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collapse and spmodel 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 collapse?
Top collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.
What are the best alternatives to spmodel?
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.