simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
kde1d vs nmar
A side-by-side editorial comparison of kde1d and nmar — release velocity, themes, recent moves, and the top alternatives to consider.
kde1d vs nmar: at a glance
What is kde1d?
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
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.
kde1d vs nmar: editorial side-by-side
kde1d
0.0ANALYTICS
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
◆ Current state
kde1d estimates univariate densities with local polynomial kernel methods, handling bounded, discrete and now zero-inflated variables through a single type argument, with the numerical work in a header-only C++ library usable outside R. Version 1.1.0 added the zero-inflated discrete-continuous mixture case and shipped a new C++ API as an explicit breaking change; 1.1.1 followed in June with auto-generated notes and no description.
◆ Where it's heading
The package has alternated between performance work and widening the class of data it accepts. The 1.0.0 release was the performance milestone — FFT-based estimation, a better integration algorithm for the p, q and r functions, deterministic jittering replacing randomness, and standalone C++ headers. The 1.1.0 release is the scope milestone, adding a third data type to the two it already handled. Releases come from the same maintainer as svines and cluster on shared dates, so changes in the underlying C++ surface across the vine and density stack tend to ship together.
◆ Prediction
With the C++ API deliberately reworked for standalone use at 1.1.0, further work most plausibly consolidates that interface rather than adding data types. What 1.1.1 actually changed is not readable from its body.
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.
Alternatives to kde1d and nmar
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 kde1d or nmar.
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 kde1d and nmar
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 agokde1dkde1d 1.1.1
- 1y agokde1dZero-inflated mixtures and a new standalone C++ API ⚡
- 4y agokde1dBit-wise Boolean operations removed
- 5y agokde1ddkde1d() invisible output fixed
- 5y agokde1dValgrind false positive silenced
- 6y agokde1dqrng dependency dropped; undefined behaviour fixed
Frequently asked questions
What is the difference between kde1d and nmar?
They serve adjacent needs but don't currently overlap on shipped themes. kde1d and nmar 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 kde1d better than nmar?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. kde1d and nmar 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 kde1d?
Top kde1d alternatives in Analytics are ranked by recent ship velocity. Browse the "kde1d alternatives" section above for the current picks, or visit /alternatives/kde1d for the full list with editorial commentary on each.
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.