fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of invasimapr and simStateSpace — release velocity, themes, recent moves, and the top alternatives to consider.
invasimapr halved its install size and became citable; the science stayed put.
invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.
State-space data simulation for R, filled in one function at a time
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.
The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.
Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.
simStateSpace generates data from state-space models — discrete-time SSM and VAR, continuous-time linear SDE and Ornstein-Uhlenbeck — for use in simulation studies of longitudinal and intensive repeated-measures designs. Recent releases add moment and intercept helpers rather than new model families: SimMVN(), the LinSDE intercept functions, and consolidation of the four separate parameter-simulation functions into one. Release notes are terse, marked Patch, and typically name one or two functions.
The package is being filled in methodically toward completeness across its four model families — whatever exists for the SSM side eventually appears for LinSDE and back again, as SSMInterceptEta/SSMInterceptY in 1.2.15 were followed by their LinSDE counterparts in 1.2.16. The other visible move was outward: bootstrap components were split into a separate bootStateSpace package, keeping this one to simulation alone. It sits in the same author's cluster of state-space and mediation packages, whose published methods papers the releases cite.
Expect the pattern to continue — small patch releases adding the missing counterpart function for a model family already served, with any larger capability likely spun out into its own package as bootstrapping was.
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 invasimapr or simStateSpace.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
See all invasimapr alternatives → · See all simStateSpace alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. invasimapr and simStateSpace 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. invasimapr and simStateSpace 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 invasimapr alternatives in Analytics are ranked by recent ship velocity. Browse the "invasimapr alternatives" section above for the current picks, or visit /alternatives/invasimapr for the full list with editorial commentary on each.
Top simStateSpace alternatives in Analytics are ranked by recent ship velocity. Browse the "simStateSpace alternatives" section above for the current picks, or visit /alternatives/simstatespace for the full list with editorial commentary on each.