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OHPL vs spmodel

A side-by-side editorial comparison of OHPL and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.

OHPL vs spmodel: at a glance

FeatureOHPLspmodel
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeschemometrics, variable-selection, spectroscopy, archival-maintenancespatial-statistics, regression-modelling, kriging, r-package
Last editorial update42m ago3h ago
WebsiteVisit →Visit →

What is OHPL?

A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.

OHPL implements ordered homogeneity pursuit lasso, a variable selection method for high-dimensional spectroscopic data that groups correlated predictors before applying a lasso. The functional package was complete by 1.2 in 2017, when prediction, performance evaluation and simulated data generation functions were added. Every release since has touched documentation and packaging only.

Read the full OHPL trajectory →

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.

Read the full spmodel trajectory →

OHPL vs spmodel: editorial side-by-side

O
OHPL
ANALYTICS
0.0

A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.

◆ Current state

OHPL implements ordered homogeneity pursuit lasso, a variable selection method for high-dimensional spectroscopic data that groups correlated predictors before applying a lasso. The functional package was complete by 1.2 in 2017, when prediction, performance evaluation and simulated data generation functions were added. Every release since has touched documentation and packaging only.

◆ Where it's heading

This is a published-method package in the archival phase: the algorithm is fixed, the paper is cited, and the maintainer keeps it installable. The releases read as a timeline of R packaging conventions rather than of the method — tidyverse code style in 2019, roxygen2 Markdown and bibentry() in 2024, Rd HTML validation in 2026. Gaps of two to five years between releases are normal here.

◆ Prediction

Expect the next release whenever CRAN introduces another documentation or packaging check; there is no indication the method itself will be extended.

S
spmodel
ANALYTICS
0.0

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 OHPL 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 OHPL or spmodel.

See all OHPL alternatives → · See all spmodel alternatives →

Recent activity from OHPL and spmodel

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agospmodelTighter optimiser tolerance to avoid local maxima
  2. 4mo agoOHPLRd documentation HTML validation fixed
  3. 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
  4. 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
  5. 1y agospmodelBlock kriging for areal averages and their uncertainty
  6. 1y agospmodelRobust semivariogram and new covariance types for areal models
  7. 1y agospmodelRange constraint option and redefined covariance type names
  8. 2y agoOHPLDocumentation modernized to current R conventions
  9. 7y agoOHPLCode restyled and repository links updated
  10. 9y agoOHPLCitation information and documentation site updated
  11. 9y agoOHPLPrediction and evaluation functions complete the package

Frequently asked questions

What is the difference between OHPL and spmodel?

They serve adjacent needs but don't currently overlap on shipped themes. OHPL 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 OHPL better than spmodel?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. OHPL 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 OHPL?

Top OHPL alternatives in Analytics are ranked by recent ship velocity. Browse the "OHPL alternatives" section above for the current picks, or visit /alternatives/ohpl 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.