simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
collinear vs svines
A side-by-side editorial comparison of collinear and svines — release velocity, themes, recent moves, and the top alternatives to consider.
collinear vs svines: at a glance
What is collinear?
collinear has broken its API twice to stop making the user pick thresholds.
collinear removes multicollinearity from predictor sets through pairwise correlation and VIF filtering, with a preference order deciding which variable survives each conflict. Two major versions in thirteen months each rewrote the interface: 2.0.0 extended every function to any combination of categorical and numeric responses and predictors, and 3.0.0 moved to multiple responses, restructured the output into classed objects, and made both filtering thresholds adaptive by default. Version 3.0.1 is the first release since that is purely repair.
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.
collinear vs svines: editorial side-by-side
collinear
0.0ANALYTICS
collinear has broken its API twice to stop making the user pick thresholds.
◆ Current state
collinear removes multicollinearity from predictor sets through pairwise correlation and VIF filtering, with a preference order deciding which variable survives each conflict. Two major versions in thirteen months each rewrote the interface: 2.0.0 extended every function to any combination of categorical and numeric responses and predictors, and 3.0.0 moved to multiple responses, restructured the output into classed objects, and made both filtering thresholds adaptive by default. Version 3.0.1 is the first release since that is purely repair.
◆ Where it's heading
The through-line is removing decisions the user was never well placed to make. Preference-order functions were renamed twice — first onto a metric-and-model scheme in 2.0.0, then onto a response-type scheme in 3.0.0 — and f_auto() picks one when none is given; target encoding went from automatic to opt-in; max_cor and max_vif now default to NULL and trigger a data-driven threshold derived from the 75th percentile of pairwise correlations through a sigmoid and a fitted correlation-to-VIF mapping. Each change is defensible and each one broke callers, which is the cost of this approach.
◆ Prediction
3.0.1 moved the example datasets out into a separate spatialData package and fixed four crashes rather than adding anything, so the next release is most likely more consolidation on the 3.0 surface than a fourth interface.
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.
Alternatives to collinear 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 collinear or svines.
lavaanExtra
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
ibis.iSDM
A raster-to-terra migration is the only readable change in a feed of merge notes.
anyflights
A nycflights13 generator whose recent work is all about the data being right.
vinereg
Conditional density and log-likelihood fill out a vine copula regression package.
stringx
A drop-in string API for base R, kept alive by upstream check failures.
See all collinear alternatives → · See all svines alternatives →
Recent activity from collinear and svines
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agocollinearNamespace, NA and sf fixes; example data moves to spatialData
- 8mo agocollinearAdaptive thresholds, multi-response support and a new output class ⚡
- 1y agosvinessvines 0.2.7
- 1y agosvinesAdapted to new rvinecopulib version
- 1y agocollinearCategorical responses, f_auto() defaults and future-based parallelism ⚡
- 2y agosvinesPseudo residuals and logLik support added
Frequently asked questions
What is the difference between collinear and svines?
They serve adjacent needs but don't currently overlap on shipped themes. collinear and svines 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 collinear better than svines?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collinear and svines 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 collinear?
Top collinear alternatives in Analytics are ranked by recent ship velocity. Browse the "collinear alternatives" section above for the current picks, or visit /alternatives/collinear 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.