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Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of simStateSpace and susier — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.
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.
susieR implements the Sum of Single Effects regression model for variable selection and fine-mapping, widely used in statistical genetics. The recent releases are a tight run of correctness work concentrated in one area: null effect trimming. Version 0.15.55 fixed trimming under the Servin-Stephens residual variance method, 0.15.56 fixed it again for non-uniform prior weights fourteen minutes later, 0.15.57 corrected an ELBO null space term for RSS with X and a matrix symmetry check, and 0.15.58 addressed an alpha0/beta0 issue. Version 0.16.0 migrates the C++ bindings from Rcpp to cpp11 with cpp11armadillo.
The version-number churn understates how narrow this work is — four consecutive releases touching the same trimming and residual-variance machinery suggests one area where the implementation and the intended behavior had drifted apart. The 0.16.0 binding migration is the only structural change, and it is invisible to users while mattering for build portability and long-term maintenance. Development is clearly active, with automated release tooling and dependency bumps flowing through the same stream.
With the binding migration just landed, near-term releases are likely to address fallout from it alongside continued fixes in the same trimming and residual-variance code.
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 simStateSpace or susier.
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 simStateSpace alternatives → · See all susier alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. simStateSpace and susier 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. simStateSpace and susier 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 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.
Top susier alternatives in Analytics are ranked by recent ship velocity. Browse the "susier alternatives" section above for the current picks, or visit /alternatives/susier for the full list with editorial commentary on each.