simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
quanteda.textmodels vs tbrf
A side-by-side editorial comparison of quanteda.textmodels and tbrf — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
quanteda.textmodels vs tbrf: at a glance
What is quanteda.textmodels?
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.
What is tbrf?
Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
quanteda.textmodels vs tbrf: editorial side-by-side
quanteda.textmodels
0.0ANALYTICS
Split out of quanteda, then quiet - one new classifier since 2020.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
The next release most likely follows another upstream change in quanteda or a Matrix and Rcpp dependency rather than adding a model.
tbrf
0.0ANALYTICS
Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.
◆ Current state
tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.
◆ Where it's heading
The package spent its middle releases absorbing upstream breakage — a lubridate duration redefinition, a tibble 3.0.0 subassignment change, tidyselect internals. The 0.1.7 release breaks that pattern: it is the first in five years to add capability rather than repair it, and it does so by internalising a stat from an abandoned dependency instead of relying on it. Cadence remains very low, with a five-year gap between 0.1.5 and 0.1.6.
◆ Prediction
Absorbing stat_stepribbon() directly suggests further vendoring of the plotting layer rather than new statistical functions. The entries do not indicate which rolling statistics, if any, are queued next.
Alternatives to quanteda.textmodels and tbrf
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 quanteda.textmodels or tbrf.
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.
See all quanteda.textmodels alternatives → · See all tbrf alternatives →
Recent activity from quanteda.textmodels and tbrf
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 0y agotbrfstat_stepribbon vendored in, plus na.pad on all rolling functions
- 1y agotbrfgm_mean_ci forwards na.rm and zero.propagate correctly
- 1y agoquanteda.textmodelsNamespace fixed after quanteda dropped RcppArmadillo
- 3y agoquanteda.textmodelsCRAN issues and documentation fixed
- 3y agoquanteda.textmodelsCompatibility with Matrix 1.4.2
- 5y agoquanteda.textmodelsDuplicate example dfm removed
- 5y agoquanteda.textmodelsSVM default switched to the L2-regularized dual solver
- 5y agoquanteda.textmodelsLogistic regression classifier added; svmlin rewritten in C++ ⚡
- 6y agotbrfFix internals broken by tibble 3.0.0 subassignment
- 6y agotbrfDate windows recomputed with intervals and periods
Frequently asked questions
What is the difference between quanteda.textmodels and tbrf?
Both compete on the same themes — r-package — within Analytics. quanteda.textmodels and tbrf 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 quanteda.textmodels better than tbrf?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. quanteda.textmodels and tbrf 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 quanteda.textmodels?
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.
What are the best alternatives to tbrf?
Top tbrf alternatives in Analytics are ranked by recent ship velocity. Browse the "tbrf alternatives" section above for the current picks, or visit /alternatives/tbrf for the full list with editorial commentary on each.