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haze vs svines

A side-by-side editorial comparison of haze and svines — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

haze vs svines: at a glance

Featurehazesvines
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesneuroimaging, mesh-processing, interpolation, r-packagevine-copulas, time-series, dependence-modelling, rcpp
Last editorial update7h ago1h ago
WebsiteVisit →Visit →

What is haze?

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

Read the full haze trajectory →

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.

Read the full svines trajectory →

haze vs svines: editorial side-by-side

H
haze
ANALYTICS
2.5

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

◆ Current state

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

◆ Where it's heading

The July 2026 release arrived 56 minutes after its sibling regfusionr 0.3.0 from the same maintainer, which is the tell: this is a maintainer sweeping a set of related neuroimaging packages back into working order, not independent development on haze itself. haze is the dependency, regfusionr the consumer, and the substantive work sits on the regfusionr side. The off-by-one correction is the only change here that alters results.

◆ Prediction

Expect haze to move only when a downstream dfsp-spirit package needs it to — its cadence is driven by the sibling packages, not by its own roadmap.

S
svines
ANALYTICS
0.0

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.

Alternatives to haze and svines

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 haze or svines.

See all haze alternatives → · See all svines alternatives →

Recent activity from haze and svines

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 18d agohazeVersion 0.3.0 -- Fixes and modernization
  2. 1y agosvinessvines 0.2.7
  3. 1y agosvinesAdapted to new rvinecopulib version
  4. 2y agosvinesPseudo residuals and logLik support added
  5. 4y agohazev0.2.0 -- kdtrees
  6. 4y agohazev0.1.0: Initial release

Frequently asked questions

What is the difference between haze and svines?

Both compete on the same themes — r-package — within Analytics. haze is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is haze better than svines?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. haze is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to haze?

Top haze alternatives in Analytics are ranked by recent ship velocity. Browse the "haze alternatives" section above for the current picks, or visit /alternatives/haze for the full list with editorial commentary on each.

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.