STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
bootStateSpace vs mev
A side-by-side editorial comparison of bootStateSpace and mev — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bootStateSpace vs mev: at a glance
| Feature | bootStateSpace | mev |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | state-space-models, parametric-bootstrap, psychometrics, continuous-time-models | extreme-value-theory, threshold-selection, statistical-estimation, api-redesign |
| Last editorial update | 1h ago | 1h ago |
| Website | Visit → | Visit → |
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 mev?
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
bootStateSpace vs mev: 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.
mev
0.0ANALYTICS
An extreme-value toolkit reorganised its whole API into prefixed families and tripled its estimator count.
◆ Current state
mev provides likelihood-based inference for univariate and multivariate extreme value models — threshold selection, shape estimation, tail dependence and max-stable simulation. Version 2.0 was a deliberate reorganisation: every threshold-selection routine now carries a thselect. prefix, every stability plot a tstab. prefix, and every extremal-dependence measure an xdep. prefix, with the old names deprecated but mostly still working. The same release added a large batch of estimators — Stein-weighted GPD, roughly a dozen shape estimators, second-order regular variation, L-moment GPD and Weissman quantiles.
◆ Where it's heading
The package is consolidating into a reference implementation of the extreme-value literature rather than a collection of one-off routines. Sixteen threshold-selection methods now share standardised arguments and their own plot and print methods with automatic selection, which is the tell: the goal is comparability across methods, not just availability. Dependency reduction runs alongside, with distribution functions written in-package to drop evd and Rsolnp replacing nloptr in earlier releases.
◆ Prediction
Version 2.1 continued adding threshold-selection routines within the new naming scheme, so the next release most likely follows the same pattern — more estimators fitted to the established prefixes, plus fixes to the 2.0 renaming. The entries give no sign of a further structural change.
Alternatives to bootStateSpace and mev
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 mev.
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 mev alternatives →
Recent activity from bootStateSpace and mev
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 9mo agomevTwo more threshold-selection routines slot into the new scheme
- 9mo agomevThreshold, stability and dependence functions regrouped under prefixes ⚡
- 10mo agobootStateSpaceCitation added for the continuous-time mediation paper
- 1y agobootStateSpaceclean argument added across the four bootstrap functions
- 1y agobootStateSpaceInitial CRAN release of the state-space bootstrap sampler
- 2y agomevBoundary-case likelihood fixes, bundled with the prior release's notes
- 3y agomevGEV and GP distribution functions brought in-house to drop evd
- 4y agomevFour max-stable families, fixed parameters and threshold diagnostics
Frequently asked questions
What is the difference between bootStateSpace and mev?
Both compete on the same themes — r-package — within Analytics. bootStateSpace and mev 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 mev?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bootStateSpace and mev 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 mev?
Top mev alternatives in Analytics are ranked by recent ship velocity. Browse the "mev alternatives" section above for the current picks, or visit /alternatives/mev for the full list with editorial commentary on each.