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Comparison · Analytics
modeltime.resample vs spatstat.random
A side-by-side editorial comparison of modeltime.resample and spatstat.random — release velocity, themes, recent moves, and the top alternatives to consider.
modeltime.resample vs spatstat.random: 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 spatstat.random?
spatstat's simulation engine pushes point process generation into three dimensions
spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.
modeltime.resample vs spatstat.random: 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.
spatstat.random
2.5ANALYTICS
spatstat's simulation engine pushes point process generation into three dimensions
◆ Current state
spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.
◆ Where it's heading
The clearest arc is dimensional. 3.5-0 carried inhomogeneous Poisson processes, non-uniform random points and Simple Sequential Inhibition into 3D in a single release, and the sibling geometry package followed two months later with more capabilities for three-dimensional point patterns. Alongside that, the generators have been gaining theoretical range — Gaussian random fields in 3.4-4, a new class of theoretical cluster process models and random diffusion in 3.5-0 — while earlier releases concentrated on conditional simulation and efficiency in the existing 2D routines.
◆ Prediction
Expect the 3D work to continue propagating into the model-fitting and geometry packages before spatstat.random adds another dimension-independent generator, since the 3D features here have already begun appearing downstream. The entries do not indicate which estimator gets 3D support next.
Alternatives to modeltime.resample and spatstat.random
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 spatstat.random.
kernelshap
kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.
filtro
filtro moves to S7 and multiplies its feature-scoring methods in a single release.
modeltime.ensemble
modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.
shapviz
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
hstats
hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.
See all modeltime.resample alternatives → · See all spatstat.random alternatives →
Recent activity from modeltime.resample and spatstat.random
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agospatstat.randomEdge-effect-free random Dirichlet-Voronoi tessellation
- 2mo agospatstat.randomThree-dimensional point process simulation arrives ⚡
- 6mo agospatstat.randomGaussian random field generation added
- 10mo agospatstat.randomrunifdisc efficiency and fixed-count simulation options
- 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
- 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
- 1y agospatstat.randomConditional simulation for the cluster process generators
- 1y agospatstat.randomFaster rpoispp for tessellation-defined intensity
- 3y agomodeltime.resampleFixes workflows in regression mode
- 4y agomodeltime.resampleUpdates for hardhat 1.0.0
Frequently asked questions
What is the difference between modeltime.resample and spatstat.random?
They serve adjacent needs but don't currently overlap on shipped themes. spatstat.random is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 spatstat.random?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.random is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 spatstat.random?
Top spatstat.random alternatives in Analytics are ranked by recent ship velocity. Browse the "spatstat.random alternatives" section above for the current picks, or visit /alternatives/spatstat-random for the full list with editorial commentary on each.