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nmar vs TidyDensity

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

nmar vs TidyDensity: at a glance

FeaturenmarTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessurvey statistics, nonresponse, empirical likelihood, bootstrapstatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

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.

Read the full nmar trajectory →

What is TidyDensity?

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

Read the full TidyDensity trajectory →

nmar vs TidyDensity: editorial side-by-side

N
nmar
ANALYTICS
0.0

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.

T
TidyDensity
ANALYTICS
0.0

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

◆ Current state

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

◆ Where it's heading

The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.

◆ Prediction

The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.

Alternatives to nmar and TidyDensity

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 TidyDensity.

See all nmar alternatives → · See all TidyDensity alternatives →

Recent activity from nmar and TidyDensity

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

  1. 6mo agonmarBootstrap backend now parallel-aware and configurable
  2. 7mo agonmarCRAN submission fixes and DOI references
  3. 8mo agonmarNMAR 0.1.0
  4. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  5. 1y agoTidyDensityDocumentation corrections for two distribution functions
  6. 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  7. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  8. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  9. 2y agoTidyDensityDistributions convertible to time series objects

Frequently asked questions

What is the difference between nmar and TidyDensity?

They serve adjacent needs but don't currently overlap on shipped themes. nmar and TidyDensity 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 TidyDensity?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. nmar and TidyDensity 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 TidyDensity?

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