STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
bootStateSpace vs sdsfun
A side-by-side editorial comparison of bootStateSpace and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bootStateSpace vs sdsfun: at a glance
What is bootStateSpace?
A parametric bootstrap for state-space models, shipped and then left alone.
bootStateSpace generates parametric bootstrap samples for state-space models, covering fixed-parameter variants across general state-space, Ornstein-Uhlenbeck, linear stochastic differential equation and vector autoregressive specifications. Its entire public history is three releases: an initial CRAN publication in January 2025, one patch adding a clean argument to the four fitting functions a month later, and a citation update in October. The methodological anchor is continuous-time mediation work published in Psychological Methods.
What is sdsfun?
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
bootStateSpace vs sdsfun: editorial side-by-side
bootStateSpace
0.0ANALYTICS
A parametric bootstrap for state-space models, shipped and then left alone.
◆ Current state
bootStateSpace generates parametric bootstrap samples for state-space models, covering fixed-parameter variants across general state-space, Ornstein-Uhlenbeck, linear stochastic differential equation and vector autoregressive specifications. Its entire public history is three releases: an initial CRAN publication in January 2025, one patch adding a clean argument to the four fitting functions a month later, and a citation update in October. The methodological anchor is continuous-time mediation work published in Psychological Methods.
◆ Where it's heading
This is research software following its paper rather than a product on a roadmap — the most recent release adds nothing but a citation to the 2025 Psychological Methods article on effects in continuous-time mediation models. It sits within the same author's cluster of psychometric and continuous-time modelling packages, which is where changes to the underlying methods tend to originate. The package itself has been functionally unchanged since February 2025.
◆ Prediction
The release pattern suggests the package moves when the associated research does, so the next change most likely accompanies a new paper or a fix surfaced by a sibling package rather than arriving on its own schedule.
sdsfun
0.0ANALYTICS
A spatial-statistics utility package exists to be depended on, and is built accordingly.
◆ Current state
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
◆ Where it's heading
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
◆ Prediction
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
Alternatives to bootStateSpace and sdsfun
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 bootStateSpace or sdsfun.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all bootStateSpace alternatives → · See all sdsfun alternatives →
Recent activity from bootStateSpace and sdsfun
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agobootStateSpaceCitation added for the continuous-time mediation paper
- 10mo agosdsfunPackage load stops touching the RNG state
- 1y agosdsfunUnified partial correlation testing and head/tails discretization
- 1y agobootStateSpaceclean argument added across the four bootstrap functions
- 1y agobootStateSpaceInitial CRAN release of the state-space bootstrap sampler
- 1y agosdsfunMissing-value handling added to linear trend removal
- 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
- 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
- 1y agosdsfunFast geodetector q-value estimator added
Frequently asked questions
What is the difference between bootStateSpace and sdsfun?
Both compete on the same themes — r-package — within Analytics. bootStateSpace and sdsfun 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.
Is bootStateSpace better than sdsfun?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bootStateSpace and sdsfun 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.
What are the best alternatives to bootStateSpace?
Top bootStateSpace alternatives in Analytics are ranked by recent ship velocity. Browse the "bootStateSpace alternatives" section above for the current picks, or visit /alternatives/bootstatespace for the full list with editorial commentary on each.
What are the best alternatives to sdsfun?
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.