STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of reda and reliagrowr — release velocity, themes, recent moves, and the top alternatives to consider.
A mature recurrent-event toolkit in careful maintenance, shedding weight rather than adding surface.
reda provides nonparametric mean cumulative function estimation, gamma-frailty rate regression, and event-data simulation for recurrent-event survival analysis. The core API settled at 0.5.0 when Recur() replaced Survr() and the MCF internals moved to C++. Everything since has been consolidation: small argument additions, method completions, and CRAN hygiene.
A reliability growth package put its models behind an MCP server for AI assistants to call.
ReliaGrowR fits reliability growth models to failure data — Crow-AMSAA and Duane, with maximum likelihood estimation, confidence bounds, prediction, and reliability demonstration test planning. The last year widened it well past growth curves into repairable systems: parametric non-homogeneous Poisson process fitting with automatic change point detection, non-parametric mean cumulative function estimation, and system exposure calculation. The most recent release adds goodness-of-fit statistics and exposes the package's functions as Model Context Protocol tools.
reda provides nonparametric mean cumulative function estimation, gamma-frailty rate regression, and event-data simulation for recurrent-event survival analysis. The core API settled at 0.5.0 when Recur() replaced Survr() and the MCF internals moved to C++. Everything since has been consolidation: small argument additions, method completions, and CRAN hygiene.
The last three releases contain no new modelling capability at all — a dependency reshuffle, a test-example correction, and a print-order fix. The package is being kept installable and correct rather than extended. Its tightest coupling is to splines2, a sibling package from the same maintainer, which supplies the derivative machinery reda depends on.
Expect continued small-cadence CRAN-compliance releases tracking ggplot2 and splines2 changes. The entries show no in-progress feature work, so a substantive release would have to arrive without warning from this feed.
ReliaGrowR fits reliability growth models to failure data — Crow-AMSAA and Duane, with maximum likelihood estimation, confidence bounds, prediction, and reliability demonstration test planning. The last year widened it well past growth curves into repairable systems: parametric non-homogeneous Poisson process fitting with automatic change point detection, non-parametric mean cumulative function estimation, and system exposure calculation. The most recent release adds goodness-of-fit statistics and exposes the package's functions as Model Context Protocol tools.
Two arcs run in parallel. The statistical one is a steady march from plotting a growth curve to modelling recurrent failures properly — segmented NHPP models that detect their own change points, Nelson-Aalen estimation, Cramér-von Mises and Kolmogorov-Smirnov statistics for judging the fits. The interface one is newer and more unusual: the package now ships an MCP server, and its sibling plotting package followed with one two weeks later, so this is a deliberate direction across the maintainer's reliability suite rather than a single experiment. Naming and S3 conventions were cleaned up early, which is what made a uniform tool surface plausible later.
Given the sibling packages moved to MCP within weeks of each other, the remaining tools in the suite are the obvious next candidates; on the statistical side, goodness-of-fit having just arrived suggests model comparison and selection helpers are the natural follow-on.
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 reda or reliagrowr.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all reda alternatives → · See all reliagrowr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. reda and reliagrowr 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. reda and reliagrowr 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 reda alternatives in Analytics are ranked by recent ship velocity. Browse the "reda alternatives" section above for the current picks, or visit /alternatives/reda for the full list with editorial commentary on each.
Top reliagrowr alternatives in Analytics are ranked by recent ship velocity. Browse the "reliagrowr alternatives" section above for the current picks, or visit /alternatives/reliagrowr for the full list with editorial commentary on each.