rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of epiflows and lpjmlkit — release velocity, themes, recent moves, and the top alternatives to consider.
epiflows has shipped four releases in eight years, none of which changed the code.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
The LPJmL toolkit finally reads NetCDF, closing a gap against the format its field uses.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
epiflows predicts the spread of infectious disease along population flows between locations, and it is effectively dormant. The whole visible history spans 2018 to 2026 in four entries: the first CRAN release, a Zenodo archival tag, a Roxygen patch whose notes state the functionality is unchanged, and a 2026 release replacing deprecated ggplot2 and tibble calls. No entry describes new epidemiological capability.
The package is being kept installable rather than developed. The one recent release is dependency maintenance contributed from outside, which is the pattern for RECON-era epidemiology packages that have outlived their original project funding. Two separate entries are both labelled version 0.2.1, so even the version history is not a reliable guide to what changed.
Any further releases will most likely be more deprecation cleanup to keep the package on CRAN; there is nothing in the record suggesting active development has resumed.
lpjmlkit is the R toolkit for running the LPJmL dynamic global vegetation model and reading its output. The 1.8.0 release adds direct NetCDF reading, either straight or via .nc.json metafiles, alongside the package's own binary formats. Before that, 1.7.3 sped up read_io(), reworked the LPJmLGridData implementation and added reservoir input support. Releases are infrequent, roughly one every 12 to 18 months.
The work concentrates on the I/O layer rather than the modeling interface, and it is moving toward the formats the wider earth-system community already exchanges. The gap between 1.7.3 and 1.8.0 is over a year, so this is a research-group package released when the science requires it, not on a schedule. The changelog itself is thin — several entries are merge-commit text or CRAN resubmissions.
Further I/O breadth is the likeliest direction now that NetCDF is supported, though the entries give no schedule; the release cadence has not been regular enough to predict timing.
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 epiflows or lpjmlkit.
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
SimInf 10.0 turns an epidemic simulator into a tool that fits models to real time series
A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release
A statistician's personal toolbox, growing one plotting utility at a time
R/qtl is in pure custodial mode: every recent release answers a compiler, not a user
See all epiflows alternatives → · See all lpjmlkit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r — within Analytics. epiflows and lpjmlkit 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. epiflows and lpjmlkit 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 epiflows alternatives in Analytics are ranked by recent ship velocity. Browse the "epiflows alternatives" section above for the current picks, or visit /alternatives/epiflows-r for the full list with editorial commentary on each.
Top lpjmlkit alternatives in Analytics are ranked by recent ship velocity. Browse the "lpjmlkit alternatives" section above for the current picks, or visit /alternatives/lpjmlkit-r for the full list with editorial commentary on each.