rjdqa
rjdqa keeps refining one screen: the seasonal adjustment quality dashboard
A side-by-side editorial comparison of biocro and weird — release velocity, themes, recent moves, and the top alternatives to consider.
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
BioCro is a C++ crop growth simulator with an R interface, built from swappable modules for photosynthesis, respiration and development. Version 3.3.0 added multidimensional and one-dimensional root finders to the C++ source and put them to work immediately, replacing the fixed-point iteration used for intercellular CO2 with a Dekker root finder on the grounds that fixed-point iteration is known to be unstable there. Getting to that release also required moving from C++11 to C++17 and updating the bundled boost from 1.71 to 1.89.
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
BioCro is a C++ crop growth simulator with an R interface, built from swappable modules for photosynthesis, respiration and development. Version 3.3.0 added multidimensional and one-dimensional root finders to the C++ source and put them to work immediately, replacing the fixed-point iteration used for intercellular CO2 with a Dekker root finder on the grounds that fixed-point iteration is known to be unstable there. Getting to that release also required moving from C++11 to C++17 and updating the bundled boost from 1.71 to 1.89.
Two threads run together: the biology is being broken into finer interchangeable modules — separate maintenance respiration, alternative linear and logistic SLA methods, a direct development-index module — while the numerics underneath are being made solvable in general. The root finders are explicitly staged to move into the shared biocro/framework repository, so this is groundwork for other models rather than for this package alone.
More module-level alternatives that depend on simultaneous-equation solutions are the natural follow-on, and the root finders should migrate out to biocro/framework as the notes state.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
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 biocro or weird.
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 biocro alternatives → · See all weird alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. biocro and weird 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. biocro and weird 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 biocro alternatives in Analytics are ranked by recent ship velocity. Browse the "biocro alternatives" section above for the current picks, or visit /alternatives/biocro-r for the full list with editorial commentary on each.
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.