rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
modeldata vs posterior
A side-by-side editorial comparison of modeldata and posterior — release velocity, themes, recent moves, and the top alternatives to consider.
modeldata vs posterior: at a glance
What is modeldata?
The tidymodels example-data package grows one dataset at a time, on nobody's schedule
modeldata exists to supply the datasets and simulation functions that tidymodels documentation, tests, and teaching material depend on. Releases arrive roughly once or twice a year and consist almost entirely of new data sets plus occasional simulation methods. The most recent work adds a Worley (1987) regression simulation and moves the package off the magrittr pipe onto base R's.
What is posterior?
posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.
The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.
modeldata vs posterior: editorial side-by-side
modeldata
0.0ANALYTICS
The tidymodels example-data package grows one dataset at a time, on nobody's schedule
◆ Current state
modeldata exists to supply the datasets and simulation functions that tidymodels documentation, tests, and teaching material depend on. Releases arrive roughly once or twice a year and consist almost entirely of new data sets plus occasional simulation methods. The most recent work adds a Worley (1987) regression simulation and moves the package off the magrittr pipe onto base R's.
◆ Where it's heading
Two lines run through the history: broadening coverage of task types — ordinal classification, multinomial, regression, QSAR-style chemistry data — and building out synthetic simulation so tutorials can demonstrate a method without shipping a real dataset for it. The simulation side has grown from a single regression generator into a family with logistic and multinomial variants and a keep_truth option that exposes the error-free outcome. Infrastructure changes appear only when the wider tidyverse moves, as the base-pipe transition shows.
◆ Prediction
The pattern points to another simulation method or a dataset filling a task type the collection still lacks, rather than any change in what the package does.
posterior
0.0ANALYTICS
posterior keeps deepening two things: the rvar type and Pareto-based diagnostics.
◆ Current state
The releases in this window advance on two fronts. The rvar random-variable type gained factor and ordered subtypes (1.4.0), rvar-indexed slicing and `rvar_ifelse()` (1.5.0), base `%*%` matrix multiplication and indexed variable names (1.6.0). Separately, Pareto diagnostics have grown from `pareto_smooth()` options and individual `pareto_khat()`-family functions (1.6.0) through `pit()` for draws and rvars (1.6.1) to exported generalized-Pareto functions and `pareto_pit` (1.7.0). 1.7.1 is a paperwork release for a JOSS submission.
◆ Where it's heading
posterior is positioning itself as shared infrastructure rather than an end-user package: 1.7.0 explicitly exports generalized-Pareto machinery 'for use in other packages', and the JOSS paper is a citation vehicle for the same audience. The rvar work points the same way — a random-variable type other Bayesian packages can build on. Cadence is steady but unhurried, roughly one feature release a year.
◆ Prediction
More diagnostic functions are likely to be exported for downstream reuse, following the pattern 1.7.0 established with the generalized-Pareto helpers.
Alternatives to modeldata and posterior
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 modeldata or posterior.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all modeldata alternatives → · See all posterior alternatives →
Recent activity from modeldata and posterior
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoposteriorposterior 1.7.1 released for JOSS paper
- 3mo agoposteriorposterior 1.7.0 exports generalized-Pareto functions
- 10mo agoposteriorposterior 1.6.1 adds pit() for draws and rvars
- 11mo agomodeldatamodeldata 1.5.1 fixes documentation and column-name typos
- 1y agomodeldatamodeldata 1.5.0 adds a Worley (1987) regression simulation
- 1y agoposteriorposterior 1.6.0 adds Pareto diagnostics and ESS-based thinning
- 2y agomodeldatamodeldata 1.4.0 adds the cat_adoption data set
- 2y agomodeldatamodeldata 1.3.0 adds the deliveries data set
- 2y agoposteriorposterior 1.5.0 adds nested-Rhat and rvar indexing
- 3y agomodeldatamodeldata 1.2.0 adds eight data sets across regression and classification
- 3y agoposteriorposterior 1.4.0 adds factor and ordered rvar subtypes
- 3y agomodeldatamodeldata 1.1.0 adds logistic and multinomial simulation plus keep_truth
Frequently asked questions
What is the difference between modeldata and posterior?
They serve adjacent needs but don't currently overlap on shipped themes. modeldata and posterior 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 modeldata better than posterior?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modeldata and posterior 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 modeldata?
Top modeldata alternatives in Analytics are ranked by recent ship velocity. Browse the "modeldata alternatives" section above for the current picks, or visit /alternatives/modeldata for the full list with editorial commentary on each.
What are the best alternatives to posterior?
Top posterior alternatives in Analytics are ranked by recent ship velocity. Browse the "posterior alternatives" section above for the current picks, or visit /alternatives/posterior for the full list with editorial commentary on each.