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Comparison · Analytics
bpbounds vs spmodel
A side-by-side editorial comparison of bpbounds and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
bpbounds vs spmodel: at a glance
What is bpbounds?
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.
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.
bpbounds vs spmodel: editorial side-by-side
bpbounds
0.0ANALYTICS
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
◆ Current state
bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.
◆ Where it's heading
The direction is toward agreement with the reference Stata implementation and away from silently wrong output. The clamping change is described as matching the same fix in the Stata package, which suggests the two implementations are being reconciled rather than developed independently. The cell-ordering defect is the more instructive one: it was fixed in the calculation function in 0.1.7 and then again in the constraint matrix in 0.1.8, meaning the same x=0,y=1 / x=1,y=0 swap had been written in two places.
◆ Prediction
Since the recent fixes came from an external contributor's report and both touched the trivariate three-category path, the untested corners of that path are where further corrections would surface — but the release notes give no roadmap beyond parity with the Stata package.
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 bpbounds 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 bpbounds or spmodel.
fastplyr
A fast dplyr stand-in that keeps finding new places to skip work entirely.
trias
Belgium's invasive-species indicator toolkit is in steady refinement, one plotting edge case at a time.
icesSAG
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
dggridR
A discrete global grid generator grew cell traversal and became a usable spatial index.
vegan
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
See all bpbounds alternatives → · See all spmodel alternatives →
Recent activity from bpbounds and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agobpboundsbpbounds clamps probability bounds and fixes a constraint-matrix swap
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 2mo agobpboundsbpbounds fixes swapped cells in the trivariate calculation
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 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
- 2y agobpboundsbpbounds 0.1.6
- 3y agobpboundsbpbounds 0.1.5
- 6y agobpboundsVersion 0.1.4 on CRAN
- 7y agobpboundsVersion 0.1.3
Frequently asked questions
What is the difference between bpbounds and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. bpbounds 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 bpbounds better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bpbounds 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 bpbounds?
Top bpbounds alternatives in Analytics are ranked by recent ship velocity. Browse the "bpbounds alternatives" section above for the current picks, or visit /alternatives/bpbounds 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.