cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of epidict and SSN2 — release velocity, themes, recent moves, and the top alternatives to consider.
A spin-out dictionary reader for MSF epidemiological data, finding its shape on CRAN
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
Stream-network spatial models learning to run on data that no longer fits in memory
SSN2 fits spatial statistical models on stream networks, where covariance follows flow-connected distance along the network rather than straight-line distance. It is the maintained successor to the original SSN package, published through JOSS in 2024, and leans on spmodel for its underlying model machinery. Recent releases have concentrated on the constraint that binds this class of model hardest: the distance matrix.
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
The arc is a package being unbundled and then reassembled as its dependencies land on CRAN. The 0.1.0 release deliberately dropped msf_dict_rename_helper() because its dependencies weren't available; 0.2.0 put it back. 0.3.0 is the first release that adds rather than restores, extending intersectional dictionary support and giving callers control over name cleaning.
Expect the next releases to keep widening dictionary coverage rather than changing the API, since the reinstatement work that dominated 0.1.0 to 0.2.0 is now finished.
SSN2 fits spatial statistical models on stream networks, where covariance follows flow-connected distance along the network rather than straight-line distance. It is the maintained successor to the original SSN package, published through JOSS in 2024, and leans on spmodel for its underlying model machinery. Recent releases have concentrated on the constraint that binds this class of model hardest: the distance matrix.
The first year was about establishing credibility and interoperability — a JOSS review, geopackage import support, deprecation of the SSN-to-SSN2 bridge, marginal means through emmeans. The 2025 releases turn to scale, moving distance matrices onto disk via filematrix and routing estimation and prediction through the local approximation. The 0.4.0 default change is the visible consequence: the neighbourhood size rises from 100 to 200, buying accuracy now that the surrounding machinery can afford it.
With the large-data path established and its default just retuned, the next work most likely tightens that approximation further or extends it to the model classes the local argument does not yet cover.
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 epidict or SSN2.
A choice-based IRT model published once in 2019 and kept compiling ever since
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
See all epidict alternatives → · See all SSN2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. epidict and SSN2 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. epidict and SSN2 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 epidict alternatives in Analytics are ranked by recent ship velocity. Browse the "epidict alternatives" section above for the current picks, or visit /alternatives/epidict for the full list with editorial commentary on each.
Top SSN2 alternatives in Analytics are ranked by recent ship velocity. Browse the "SSN2 alternatives" section above for the current picks, or visit /alternatives/ssn2 for the full list with editorial commentary on each.