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Comparison · Analytics
enpls vs spmodel
A side-by-side editorial comparison of enpls and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
enpls vs spmodel: at a glance
What is enpls?
enpls has not changed its statistics since 2016 — only its website, twice.
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
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.
enpls vs spmodel: editorial side-by-side
enpls
0.0ANALYTICS
enpls has not changed its statistics since 2016 — only its website, twice.
◆ Current state
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
◆ Where it's heading
The statistical work finished around version 5.6, which added cross-validation fold control and fixed component selection when the maximum was left unspecified. Everything since has kept the package installable and its docs online. The 2025 release arriving the same day as sibling package grex, with the same two fixes, confirms the pattern: these are maintainer sweeps across a portfolio, not attention to enpls specifically.
◆ Prediction
The next release will almost certainly be another CRAN or tooling fix. Six consecutive infrastructure-only releases across nine years give no basis for expecting new methods.
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 enpls 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 enpls 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.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
protr
protr's feature set is finished; the work now is surviving Bioconductor's churn.
See all enpls alternatives → · See all spmodel alternatives →
Recent activity from enpls 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
- 1y agoenplsenpls 6.1.1 moves pkgdown to GitHub Actions
- 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
- 7y agoenplsenpls 6.1 adopts tidyverse code style
- 8y agoenplsenpls 6.0 changes the documentation URL
- 8y agoenplsenpls 5.9 drops Google Fonts from vignettes
- 9y agoenplsenpls 5.8 updates gallery images, enables HTTPS
- 9y agoenplsenpls 5.7 adds a pkgdown site and Windows CI
Frequently asked questions
What is the difference between enpls and spmodel?
Both compete on the same themes — r-package — within Analytics. enpls 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 enpls better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. enpls 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 enpls?
Top enpls alternatives in Analytics are ranked by recent ship velocity. Browse the "enpls alternatives" section above for the current picks, or visit /alternatives/enpls 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.