cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of fmtr and itp — release velocity, themes, recent moves, and the top alternatives to consider.
Rebuilding SAS's formatting layer in R, one format specification at a time
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
A single-algorithm root-finder that finished its job in 2022 and has been idling since
itp implements one thing: the Interpolate, Truncate, Project root-finding algorithm of Oliveira and Takahashi, which narrows a bracketing interval each iteration and keeps bisection's worst-case guarantee while converging faster on well-behaved functions. The package reached its intended shape within about six weeks of first release, gaining a C++ entry point and the ability to take C++ function pointers. Everything after mid-2022 is compiler and CRAN upkeep.
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
The direction is parity, pursued in small increments. Quarter format codes were added because base R has none; the SAS best. format was reimplemented, then hardened against the variations people actually write; statistical summary helpers like fmt_mean_sd() and fmt_mean_stderr() cover the cell contents clinical tables need. The structural work is largely behind it, including the breaking 2022 move that handed labelling to a sibling package, so what remains is vocabulary coverage.
The pattern of adding a SAS format, then a release to handle its variants, suggests the next releases continue filling in format codes and summary helpers rather than changing how formats are applied.
itp implements one thing: the Interpolate, Truncate, Project root-finding algorithm of Oliveira and Takahashi, which narrows a bracketing interval each iteration and keeps bisection's worst-case guarantee while converging faster on well-behaved functions. The package reached its intended shape within about six weeks of first release, gaining a C++ entry point and the ability to take C++ function pointers. Everything after mid-2022 is compiler and CRAN upkeep.
The arc is short and complete. Three releases in June and July 2022 took the package from an R implementation to one that can run the whole algorithm in C++ and accept user-supplied C++ functions via Rcpp's external pointer framework. Since then the only releases have been reactions to Rcpp changes that would otherwise trip CRAN checks — 2023 and 2026, both traceable to specific upstream Rcpp issues.
There is no visible development agenda here; the entries suggest the package surfaces only when Rcpp or CRAN check policy forces a patch.
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 fmtr or itp.
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
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Stream-network spatial models learning to run on data that no longer fits in memory
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
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fmtr and itp 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. fmtr and itp 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 fmtr alternatives in Analytics are ranked by recent ship velocity. Browse the "fmtr alternatives" section above for the current picks, or visit /alternatives/fmtr for the full list with editorial commentary on each.
Top itp alternatives in Analytics are ranked by recent ship velocity. Browse the "itp alternatives" section above for the current picks, or visit /alternatives/itp for the full list with editorial commentary on each.