← Back to home
Comparison · Analytics

bpbounds vs modeltime.resample

A side-by-side editorial comparison of bpbounds and modeltime.resample — release velocity, themes, recent moves, and the top alternatives to consider.

bpbounds vs modeltime.resample: at a glance

Featurebpboundsmodeltime.resample
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themescausal inference, instrumental variables, r, partial identificationtime series, cross-validation, tidymodels, compatibility maintenance
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is bpbounds?

bpbounds found the same swapped-cell bug twice and clamped its bounds back into range

bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.

Read the full bpbounds trajectory →

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.

Read the full modeltime.resample trajectory →

bpbounds vs modeltime.resample: editorial side-by-side

B
bpbounds
ANALYTICS
0.0

bpbounds found the same swapped-cell bug twice and clamped its bounds back into range

◆ Current state

bpbounds computes nonparametric Balke-Pearl bounds on the average causal effect from instrumental variable data, in the bivariate and trivariate cases. After years of pure packaging maintenance, the two 2026 releases are analytical corrections. Bounds on intervention probabilities are now clamped to [0, 1] so derived causal risk ratio bounds cannot fall outside their feasible range, and a cell-ordering error in the trivariate three-category instrument path has been repaired.

◆ Where it's heading

The direction is toward agreement with the reference Stata implementation and away from silently wrong output. The clamping change is described as matching the same fix in the Stata package, which suggests the two implementations are being reconciled rather than developed independently. The cell-ordering defect is the more instructive one: it was fixed in the calculation function in 0.1.7 and then again in the constraint matrix in 0.1.8, meaning the same x=0,y=1 / x=1,y=0 swap had been written in two places.

◆ Prediction

Since the recent fixes came from an external contributor's report and both touched the trivariate three-category path, the untested corners of that path are where further corrections would surface — but the release notes give no roadmap beyond parity with the Stata package.

M0.0

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.

Alternatives to bpbounds and modeltime.resample

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 bpbounds or modeltime.resample.

See all bpbounds alternatives → · See all modeltime.resample alternatives →

Recent activity from bpbounds and modeltime.resample

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agobpboundsbpbounds clamps probability bounds and fixes a constraint-matrix swap
  2. 2mo agobpboundsbpbounds fixes swapped cells in the trivariate calculation
  3. 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
  4. 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
  5. 2y agobpboundsbpbounds 0.1.6
  6. 3y agobpboundsbpbounds 0.1.5
  7. 3y agomodeltime.resampleFixes workflows in regression mode
  8. 4y agomodeltime.resampleUpdates for hardhat 1.0.0
  9. 6y agobpboundsVersion 0.1.4 on CRAN
  10. 7y agobpboundsVersion 0.1.3

Frequently asked questions

What is the difference between bpbounds and modeltime.resample?

They serve adjacent needs but don't currently overlap on shipped themes. bpbounds and modeltime.resample 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 bpbounds better than modeltime.resample?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bpbounds and modeltime.resample 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 bpbounds?

Top bpbounds alternatives in Analytics are ranked by recent ship velocity. Browse the "bpbounds alternatives" section above for the current picks, or visit /alternatives/bpbounds for the full list with editorial commentary on each.

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.