rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
modeltime.resample vs n2kanalysis
A side-by-side editorial comparison of modeltime.resample and n2kanalysis — release velocity, themes, recent moves, and the top alternatives to consider.
modeltime.resample vs n2kanalysis: at a glance
What is modeltime.resample?
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
What is n2kanalysis?
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.
modeltime.resample vs n2kanalysis: editorial side-by-side
modeltime.resample
0.0ANALYTICS
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
◆ Current state
modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.
◆ Where it's heading
Every entry here is compatibility work against something upstream — hardhat 1.0.0, workflows regression mode, then tune 2.0.0 twice. The 0.3.0 notes show a second concern emerging alongside it: making failures legible, with .notes on failed fits, actionable errors from unnest_modeltime_resamples(), and fallback logic when prediction columns go missing across versions. Reproducibility gets the same treatment through explicit seeding.
◆ Prediction
Expect the next release to track the next tidymodels breaking change, with any new work continuing on error reporting rather than resampling strategies.
n2kanalysis
0.0ANALYTICS
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
◆ Current state
n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.
◆ Where it's heading
Development is slow, institutional, and driven by the modeling needs of specific monitoring programmes rather than a product roadmap. The pattern across the window is a new model class when the ecology requires one, then a stretch of infrastructure work around storage, credentials and pipeline efficiency. The 0.4.1 release is characteristic — a credentials helper, better result retrieval, more tests and a code-style pass, with no modeling change at all. Much of the early history is recorded only as merge-commit titles, so the release record thins out the further back it goes.
◆ Prediction
Expect the next substantive release to add another INLA model variant as a monitoring programme needs it, with S3 and credential handling continuing to absorb the maintenance effort in between.
Alternatives to modeltime.resample and n2kanalysis
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 modeltime.resample or n2kanalysis.
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 modeltime.resample alternatives → · See all n2kanalysis alternatives →
Recent activity from modeltime.resample and n2kanalysis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agon2kanalysisconnect_inbo_s3() exposes temporary credentials to R
- 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
- 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
- 1y agon2kanalysisINLA models with SPDE elements supported
- 2y agon2kanalysisfit_model() made more efficient
- 3y agon2kanalysisHurdle models with imputation added
- 3y agomodeltime.resampleFixes workflows in regression mode
- 4y agomodeltime.resampleUpdates for hardhat 1.0.0
- 7y agon2kanalysisImputed data handling improvements
- 7y agon2kanalysisINLA models consolidated onto a single class
Frequently asked questions
What is the difference between modeltime.resample and n2kanalysis?
They serve adjacent needs but don't currently overlap on shipped themes. modeltime.resample and n2kanalysis 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 modeltime.resample better than n2kanalysis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modeltime.resample and n2kanalysis 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 modeltime.resample?
Top modeltime.resample alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime.resample alternatives" section above for the current picks, or visit /alternatives/modeltime-resample for the full list with editorial commentary on each.
What are the best alternatives to n2kanalysis?
Top n2kanalysis alternatives in Analytics are ranked by recent ship velocity. Browse the "n2kanalysis alternatives" section above for the current picks, or visit /alternatives/n2kanalysis for the full list with editorial commentary on each.