STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
svines vs washdata
A side-by-side editorial comparison of svines and washdata — release velocity, themes, recent moves, and the top alternatives to consider.
svines vs washdata: at a glance
What is svines?
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.
What is washdata?
washdata is a fixed survey dataset; eight years of releases have changed only its packaging.
A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.
svines vs washdata: editorial side-by-side
svines
0.0ANALYTICS
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
◆ Current state
svines fits stationary vine copula models to multivariate time series, extending the rvinecopulib engine with the serial dependence structure that makes vines usable for temporal data. The visible history is three releases carrying one real addition — pseudo-residual computation and logLik support at 0.2.2 — with the rest tracking its C++ dependency.
◆ Where it's heading
This package moves when rvinecopulib moves. The 0.2.4 release exists solely to adapt to a new rvinecopulib version, and 0.2.7 carries auto-generated GitHub release notes with no description at all. It shipped on the same day as kde1d 1.1.1, another package from the same maintainer, which is the pattern to watch: changes in the shared C++ layer surface as near-simultaneous releases across the vine family rather than as independent work.
◆ Prediction
The next release most plausibly follows another rvinecopulib update rather than adding modelling capability. Two of the three visible entries carry no substantive notes, so this feed will keep underreporting what changed.
washdata
0.0ANALYTICS
washdata is a fixed survey dataset; eight years of releases have changed only its packaging.
◆ Current state
A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.
◆ Where it's heading
Nothing is heading anywhere, and for a dataset package that is the point: the value is a citable, unchanging artifact, and the release history exists to keep it installable as R's toolchain moves. The maintenance cadence matches the maintainer's other nutrition packages, which received the same repository-refresh treatment in the same period. Note also that the tags are backfilled out of order — v0.1.0 carries a later stamp than v0.1.2.
◆ Prediction
Expect further releases only when CRAN checks or infrastructure require them; there is no indication the survey data itself will be extended.
Alternatives to svines and washdata
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 svines or washdata.
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.
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.
eiaapi
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all svines alternatives → · See all washdata alternatives →
Recent activity from svines and washdata
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agowashdataRepository and toolchain maintenance
- 1y agosvinessvines 0.2.7
- 1y agosvinesAdapted to new rvinecopulib version
- 2y agowashdataDocumentation and formatting updates
- 2y agosvinesPseudo residuals and logLik support added
- 5y agowashdataSecond release: documentation and formatting
- 8y agowashdataPre-release of the survey dataset
- 8y agowashdataFirst CRAN release of the Urban Water and Sanitation Survey
Frequently asked questions
What is the difference between svines and washdata?
They serve adjacent needs but don't currently overlap on shipped themes. svines and washdata 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 svines better than washdata?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. svines and washdata 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 svines?
Top svines alternatives in Analytics are ranked by recent ship velocity. Browse the "svines alternatives" section above for the current picks, or visit /alternatives/svines for the full list with editorial commentary on each.
What are the best alternatives to washdata?
Top washdata alternatives in Analytics are ranked by recent ship velocity. Browse the "washdata alternatives" section above for the current picks, or visit /alternatives/washdata for the full list with editorial commentary on each.