paleobuddy
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
Comparison · Analytics
protr vs spmodel
A side-by-side editorial comparison of protr and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
protr vs spmodel: at a glance
What is protr?
protr's feature set is finished; the work now is surviving Bioconductor's churn.
protr generates numerical descriptors from protein sequences for machine learning, plus alignment-based similarity between sequences. The descriptor functions have been stable for years. Recent releases divide cleanly into two kinds: extending the similarity computations to work under memory constraints, and absorbing the Bioconductor split that moved pairwise alignment out of Biostrings into pwalign.
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.
protr vs spmodel: editorial side-by-side
protr
0.0ANALYTICS
protr's feature set is finished; the work now is surviving Bioconductor's churn.
◆ Current state
protr generates numerical descriptors from protein sequences for machine learning, plus alignment-based similarity between sequences. The descriptor functions have been stable for years. Recent releases divide cleanly into two kinds: extending the similarity computations to work under memory constraints, and absorbing the Bioconductor split that moved pairwise alignment out of Biostrings into pwalign.
◆ Where it's heading
The similarity side is where the remaining engineering goes, and it follows a consistent pattern — whatever parSeqSim() gained, crossSetSim() eventually gets. Batching, verbose progress and a disk-backed variant all arrived for the single-set case first and were mirrored for the cross-set case in 1.7-1. That is a maintainer closing feature-parity gaps rather than opening new directions, and the two most recent releases contain no user-facing change at all.
◆ Prediction
Expect the next release to react to another Bioconductor or R CMD check change, which accounts for three of the last four. The similarity functions now have parity, so there is no obvious internal backlog left.
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 protr 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 protr or spmodel.
geodist
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors
errors keeps making uncertainty print the way each scientific field expects.
CMAQ
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls
enpls has not changed its statistics since 2016 — only its website, twice.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
See all protr alternatives → · See all spmodel alternatives →
Recent activity from protr and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 11mo agoprotrprotr 1.7-5 silences a Debian r-devel check note
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
- 1y agoprotrprotr 1.7-4 checks alignment dependencies upfront
- 1y agoprotrprotr 1.7-3 detects Biostrings version to find pwalign
- 2y agoprotrprotr 1.7-2 fixes citation key and vignette accessibility
- 2y agoprotrprotr 1.7-1 brings crossSetSim to parity with parSeqSim
- 2y agoprotrprotr 1.7-0 adds crossSetSim for two-set similarity
Frequently asked questions
What is the difference between protr and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. protr 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 protr better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. protr 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 protr?
Top protr alternatives in Analytics are ranked by recent ship velocity. Browse the "protr alternatives" section above for the current picks, or visit /alternatives/protr-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.