constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
A side-by-side editorial comparison of distributional and qqman — release velocity, themes, recent moves, and the top alternatives to consider.
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.
Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.
qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.
The real development window was 2014 to 2015. The 0.1.2 release did the substantive work, replacing the assumption that SNPs are evenly distributed across chromosomes and handing users control of axis limits, labels and log transformation; 0.1.3 then added annotation by p-value threshold and top-SNP-per-chromosome. After that the package stops. Notably, the archival 0.0.0 entry records that the original script had confidence intervals on QQ plots and richer highlighting than the released package ever regained.
With one packaging fix in the last decade, these entries support no prediction of further releases. The package reads as complete for its narrow purpose rather than abandoned mid-arc.
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 distributional or qqman.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
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 distributional alternatives → · See all qqman alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. distributional and qqman 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. distributional and qqman 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 distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-r for the full list with editorial commentary on each.
Top qqman alternatives in Analytics are ranked by recent ship velocity. Browse the "qqman alternatives" section above for the current picks, or visit /alternatives/qqman-r for the full list with editorial commentary on each.