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fastrg vs rempsyc

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

Shared themes:r-package

fastrg vs rempsyc: at a glance

Featurefastrgrempsyc
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesrandom-graphs, stochastic-blockmodels, network-sampling, sparse-matricesapa-formatting, psychology-research, statistical-tables, ggplot2
Last editorial update48m ago1h ago
WebsiteVisit →Visit →

What is fastrg?

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

Read the full fastrg trajectory →

What is rempsyc?

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

Read the full rempsyc trajectory →

fastrg vs rempsyc: editorial side-by-side

F
fastrg
ANALYTICS
0.0

A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.

◆ Current state

fastRG samples from generalized random dot product graphs — stochastic blockmodels, degree-corrected and overlapping variants, directed and undirected — in time proportional to the number of edges rather than nodes squared, which is what makes large sparse networks tractable. Since 0.3.1 the model is constructed and parameterised in one object, with sampling methods taking that object rather than re-specifying edge distribution at sample time.

◆ Where it's heading

The package's development has been about semantic correctness more than speed. The 0.3.1 release moved edge-distribution arguments to the constructors and reinterpreted the mixing matrix S under Bernoulli parameterisation; 0.3.2 then flipped the meaning of X and Y in directed blockmodels so outgoing and incoming factors match the edge convention, and made block sorting conditional rather than unconditional. Both are corrections to what returned values mean, not to how fast they arrive. The 2025 release is CRAN documentation linking only.

◆ Prediction

With parameterisation settled and only a documentation release since 2023, the package reads as feature-complete for its sampling families. Nothing in the entries points to additional model types being queued.

R
rempsyc
ANALYTICS
0.0

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

◆ Current state

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

◆ Where it's heading

Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.

◆ Prediction

The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.

Alternatives to fastrg and rempsyc

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 fastrg or rempsyc.

See all fastrg alternatives → · See all rempsyc alternatives →

Recent activity from fastrg and rempsyc

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

  1. 11mo agorempsycPoint labels and per-group correlations added to nice_scatter
  2. 1y agofastrgDocumentation cross-linking fixes for CRAN
  3. 1y agorempsycExcel correlation export delegated to the correlation package
  4. 2y agorempsycTable spacing control and a fix for name collision with afex
  5. 2y agorempsycStandardized coefficients switch to APA 7th edition b* notation
  6. 2y agorempsycLegend and standardization-check fixes
  7. 2y agofastrgDirected blockmodel X and Y factors swapped to match edge direction
  8. 2y agorempsycnice_table starts coercing model objects automatically
  9. 4y agofastrgfastRG 0.3.1

Frequently asked questions

What is the difference between fastrg and rempsyc?

Both compete on the same themes — r-package — within Analytics. fastrg and rempsyc 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 fastrg better than rempsyc?

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

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

What are the best alternatives to rempsyc?

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