rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
climaemet vs distributional
A side-by-side editorial comparison of climaemet and distributional — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
climaemet vs distributional: at a glance
What is climaemet?
climaemet added weather alerts and wildfire risk, then spent two years managing rate limits.
climaemet wraps Spain's AEMET meteorological API — station data, historical climate series, forecasts, and the plotting helpers that go with them. Its capability surface widened decisively in 1.4.0 with meteorological alerts and wildfire risk rasters. Everything since has been about surviving the API rather than extending it: multiple API keys, quota-aware key selection, and httr2 throttling pinned to AEMET's stated 40-connections-per-minute policy.
What is distributional?
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
climaemet vs distributional: editorial side-by-side
climaemet
0.0ANALYTICS
climaemet added weather alerts and wildfire risk, then spent two years managing rate limits.
◆ Current state
climaemet wraps Spain's AEMET meteorological API — station data, historical climate series, forecasts, and the plotting helpers that go with them. Its capability surface widened decisively in 1.4.0 with meteorological alerts and wildfire risk rasters. Everything since has been about surviving the API rather than extending it: multiple API keys, quota-aware key selection, and httr2 throttling pinned to AEMET's stated 40-connections-per-minute policy.
◆ Where it's heading
Two forces shape this package, and neither is feature demand. The first is AEMET's own churn — new response codes, a fires endpoint that switched to six risk levels returned as named factors, municipality datasets refreshed annually. The second is the maintainer's cross-package modernization, visible here as the API key store moving to tools::R_user_dir() with automatic migration, a configurable timeout, cli messaging, and an R 4.1 floor. The 1.6.0 refactor is stated as AI-assisted, matching the maintainer's other packages.
◆ Prediction
Expect the next release to track another AEMET endpoint change rather than add a data domain; the throttling and multi-key machinery suggests quota pressure is the constraint the maintainer keeps returning to.
distributional
0.0ANALYTICS
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
◆ Current state
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
◆ Where it's heading
The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.
◆ Prediction
Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.
Alternatives to climaemet and distributional
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 climaemet or distributional.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all climaemet alternatives → · See all distributional alternatives →
Recent activity from climaemet and distributional
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
- 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators ⚡
- 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
- 2mo agoclimaemetAPI keys move to R_user_dir; fire risk returns named factors
- 4mo agoclimaemetVignettes migrated to Quarto
- 5mo agodistributionalDirichlet and Horseshoe distributions added
- 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
- 7mo agoclimaemetRequest throttling pinned to AEMET's 40-per-minute policy
- 1y agoclimaemetggwindrose rebuilt on coord_radial
- 1y agoclimaemetHighest-quota API key now chosen per call
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 1y agoclimaemetWeather alerts and wildfire risk rasters added ⚡
Frequently asked questions
What is the difference between climaemet and distributional?
Both compete on the same themes — r-package — within Analytics. climaemet and distributional 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 climaemet better than distributional?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. climaemet and distributional 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 climaemet?
Top climaemet alternatives in Analytics are ranked by recent ship velocity. Browse the "climaemet alternatives" section above for the current picks, or visit /alternatives/climaemet for the full list with editorial commentary on each.
What are the best alternatives to distributional?
Top distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-r for the full list with editorial commentary on each.