nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
A side-by-side editorial comparison of cTMed and qtl2fst — release velocity, themes, recent moves, and the top alternatives to consider.
Continuous-time mediation effects get standardized centrality, six years into steady patch work
cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.
The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.
The package is filling out a matrix rather than changing shape: for each effect type there is a delta-method, a Monte Carlo and a bootstrap path, and each release closes another cell. The 2025 releases were largely externally forced — an Armadillo 15.0.x transition at CRAN, a citation addition after the Psychological Methods paper landed — which suggests the statistical core has been settled since the 1.0.6 standardization revision.
The diagonal-sigma option has now reached the standardized estimators; extending it to the remaining unstandardized variants is the obvious next cell to fill.
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
The package has settled into the role of a stable satellite of R/qtl2: it tracks the parent package's conventions rather than setting its own. The cores=0 change in 0.32 arrived alongside the identical change in qtl2convert, so the parallel-computing default is being standardized across the maintainer's packages at once. Release intervals have stretched from months to years.
Further releases will most likely mirror changes originating in R/qtl2 or CRAN checks, in the same follow-the-parent pattern as 0.24 and 0.32.
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 cTMed or qtl2fst.
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all cTMed alternatives → · See all qtl2fst alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. cTMed is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. cTMed is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top cTMed alternatives in Analytics are ranked by recent ship velocity. Browse the "cTMed alternatives" section above for the current picks, or visit /alternatives/ctmed for the full list with editorial commentary on each.
Top qtl2fst alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2fst alternatives" section above for the current picks, or visit /alternatives/qtl2fst for the full list with editorial commentary on each.