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ardlverse vs OHPL

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

ardlverse vs OHPL: at a glance

FeatureardlverseOHPL
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeseconometrics, panel-data, ardl, r-packagechemometrics, variable-selection, spectroscopy, archival-maintenance
Last editorial update47m ago2h ago
WebsiteVisit →Visit →

What is ardlverse?

An outside audit against Stata found seven errors in ardlverse's panel estimator, including regressions with no intercept.

A small R package for autoregressive distributed lag models, with only three releases on record. The first two were administrative — a CRAN version note and a Zenodo metadata update. The third, 2.0.0, is a correction release built entirely from an external audit of panel_ardl() against Stata's xtpmg, and it is the only entry here with substantive content.

Read the full ardlverse trajectory →

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 →

ardlverse vs OHPL: editorial side-by-side

A
ardlverse
ANALYTICS
0.0

An outside audit against Stata found seven errors in ardlverse's panel estimator, including regressions with no intercept.

◆ Current state

A small R package for autoregressive distributed lag models, with only three releases on record. The first two were administrative — a CRAN version note and a Zenodo metadata update. The third, 2.0.0, is a correction release built entirely from an external audit of panel_ardl() against Stata's xtpmg, and it is the only entry here with substantive content.

◆ Where it's heading

The package's direction is now set by verification against an established reference implementation rather than by feature work. The seven fixes bring panel_ardl() into strict alignment with the original Pesaran, Shin and Smith framework, and the most serious of them is structural: internal regressions used lm.fit(), which unlike lm() does not append an intercept, so every short-run regression across the PMG, MG and DFE estimators was forced through the origin. Design matrices now carry a column of ones and DFE reconstructs the grand-mean intercept to match standard fixed-effects output.

◆ Prediction

Expect the next releases to extend the same audit approach to the remaining estimators, since a package that has been validated against xtpmg on one function invites the same question about the rest.

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.

Alternatives to ardlverse and OHPL

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 ardlverse or OHPL.

See all ardlverse alternatives → · See all OHPL alternatives →

Recent activity from ardlverse and OHPL

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

  1. 1mo agoardlverseSeven panel_ardl fixes after an audit against Stata's xtpmg
  2. 4mo agoOHPLRd documentation HTML validation fixed
  3. 5mo agoardlverseZenodo metadata updated with ORCID
  4. 5mo agoardlverseardlverse v1.1.3
  5. 2y agoOHPLDocumentation modernized to current R conventions
  6. 7y agoOHPLCode restyled and repository links updated
  7. 9y agoOHPLCitation information and documentation site updated
  8. 9y agoOHPLPrediction and evaluation functions complete the package

Frequently asked questions

What is the difference between ardlverse and OHPL?

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

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

Top ardlverse alternatives in Analytics are ranked by recent ship velocity. Browse the "ardlverse alternatives" section above for the current picks, or visit /alternatives/ardlverse-r for the full list with editorial commentary on each.

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.