simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of lavaanExtra and quanteda.textmodels — release velocity, themes, recent moves, and the top alternatives to consider.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
lavaanExtra provides shorthand syntax and formatted output around lavaan structural equation models - write_lavaan() to build model strings, and nice_* functions for fit tables, plots, and modification indices. Three of the six visible releases exist only to satisfy CRAN resubmission: a unicode problem, a dependency version check, tests running without suggested packages. The substance sits in 0.1.5, 0.1.8, and 0.1.9.
Split out of quanteda, then quiet - one new classifier since 2020.
quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.
lavaanExtra provides shorthand syntax and formatted output around lavaan structural equation models - write_lavaan() to build model strings, and nice_* functions for fit tables, plots, and modification indices. Three of the six visible releases exist only to satisfy CRAN resubmission: a unicode problem, a dependency version check, tests running without suggested packages. The substance sits in 0.1.5, 0.1.8, and 0.1.9.
The package generalises its own vocabulary as it goes: lavaan_ind() became lavaan_defined() once it turned out to extract any user-defined parameter, and lavaan_cov() was split so lavaan_cor() covers actual correlations. Methodological positions are taken alongside the API - dropping the estimate argument from lavaan_reg() to force reporting both standardized and unstandardized values, and updating the RMSEA benchmark to Schreiber (2017). Rémi Thériault maintains it next to rempsyc, which formats output to match. Note that 0.1.5 restates the whole 0.1.4.x development series in one body.
The pattern points to another nice_* helper aimed at a reporting step that currently needs hand formatting, arriving with the usual CRAN resubmission behind it.
quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.
The package now moves when its parent or a dependency moves, not on its own schedule. Four of the six most recent releases exist to track changes in quanteda, Matrix, or CRAN policy. The modelling decisions that were made - defaulting textmodel_svm() to the L2-regularized L2-loss dual solver, reducing svmlin to a single algorithm - have not been revisited since.
The next release most likely follows another upstream change in quanteda or a Matrix and Rcpp dependency rather than adding a model.
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 lavaanExtra or quanteda.textmodels.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
From a bundled hospital dataset to a live CMS API client.
See all lavaanExtra alternatives → · See all quanteda.textmodels alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. lavaanExtra and quanteda.textmodels 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. lavaanExtra and quanteda.textmodels 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.
Top lavaanExtra alternatives in Analytics are ranked by recent ship velocity. Browse the "lavaanExtra alternatives" section above for the current picks, or visit /alternatives/lavaanextra for the full list with editorial commentary on each.
Top quanteda.textmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "quanteda.textmodels alternatives" section above for the current picks, or visit /alternatives/quanteda-textmodels for the full list with editorial commentary on each.