constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
Comparison · Analytics
qqman vs spmodel
A side-by-side editorial comparison of qqman and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
qqman vs spmodel: at a glance
What is qqman?
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.
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.
qqman vs spmodel: editorial side-by-side
qqman
0.0ANALYTICS
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
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 qqman 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 qqman or spmodel.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all qqman alternatives → · See all spmodel alternatives →
Recent activity from qqman 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 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
- 9y agoqqmanREADME image path fix for pandoc
- 11y agoqqmanAnnotate SNPs by p-value threshold or per-chromosome top hit
- 11y agoqqmanChromosome ticks stop assuming even SNP spacing; axis control opens up
- 12y agoqqmanArchival tag for the pre-package standalone script
- 12y agoqqmanVignette touch-up
- 12y agoqqmanZenodo archival tag, no code change
Frequently asked questions
What is the difference between qqman and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. qqman 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 qqman better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qqman 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 qqman?
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.
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.