qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of constants and enpls — release velocity, themes, recent moves, and the top alternatives to consider.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
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.
constants exposes the CODATA recommended values of the physical constants to R, as a data frame plus symbol lists that carry units, uncertainties, or both. The package reached 1.0.0 on the 2018 CODATA release and has shipped once since, purely to track a units package update. Its surface is small and its release cadence is bound to CODATA, which revises every few years.
The direction set at 1.0.0 was to stop being a curated convenience wrapper and become a mechanical mirror of NIST. Hand-crafted symbol names were replaced with NIST's own ASCII symbols, categories adopted NIST's, and uncertainty switched from relative to absolute — all framed by the maintainer as necessary to make future CODATA updates routine. On top of that the package gained a correlation matrix and optional integration with the quantities package, moving it from a lookup table toward something that can propagate uncertainty.
Having rebuilt the symbol table specifically so CODATA revisions become mechanical, the next substantive release most likely tracks a new CODATA dataset rather than adding API. The experimental correlated-value support, disabled by default at 1.0.0, is the one part these entries flag as unfinished.
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.
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.
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.
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 constants or enpls.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all constants alternatives → · See all enpls alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. constants and enpls 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. constants and enpls 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.
Top constants alternatives in Analytics are ranked by recent ship velocity. Browse the "constants alternatives" section above for the current picks, or visit /alternatives/constants-r for the full list with editorial commentary on each.
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.