simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
nmar vs svines
A side-by-side editorial comparison of nmar and svines — release velocity, themes, recent moves, and the top alternatives to consider.
nmar vs svines: at a glance
What is nmar?
NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
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.
nmar vs svines: editorial side-by-side
nmar
0.0ANALYTICS
NMAR landed on CRAN with two nonresponse estimators behind one interface, then started tuning it.
◆ Current state
Three releases in seven weeks, starting from nothing. The initial CRAN release implements empirical likelihood (Qin, Leung and Shao 2002) and both parametric and nonparametric exponential tilting (Riddles, Kim and Im 2016) for estimating means under nonignorable nonresponse, all reachable through a single nmar() call with formula syntax and direct support for survey.design objects. Since then the work has been operational: a configurable bootstrap backend and stricter input validation.
◆ Where it's heading
The package is positioning itself as the general interface to nonignorable-nonresponse estimation rather than a reference implementation of one paper — shared architecture across engines, one formula API, and integration with the survey package so weights and stratification come for free. The follow-up releases suggest the next constraint is compute: bootstrap variance estimation is the expensive part, and it now dispatches to future.apply when a parallel plan exists.
◆ Prediction
Expect further engines under the same nmar() interface or wider bootstrap support, since the architecture was explicitly refactored to share structure across estimators.
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 nmar 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 nmar 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.
Recent activity from nmar and svines
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agonmarBootstrap backend now parallel-aware and configurable
- 7mo agonmarCRAN submission fixes and DOI references
- 8mo agonmarNMAR 0.1.0 ⚡
- 1y agosvinessvines 0.2.7
- 1y agosvinesAdapted to new rvinecopulib version
- 2y agosvinesPseudo residuals and logLik support added
Frequently asked questions
What is the difference between nmar and svines?
They serve adjacent needs but don't currently overlap on shipped themes. nmar 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 nmar better than svines?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nmar 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 nmar?
Top nmar alternatives in Analytics are ranked by recent ship velocity. Browse the "nmar alternatives" section above for the current picks, or visit /alternatives/nmar 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.