ANALYTICS
Pattern fills for ggplot2, hardened against the ways users write sizes
Alternatives · analytics tools
spEDM alternatives
The best spEDM alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 17, 2026
Looking for the best alternatives to spEDM? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, spEDM shipped 0 meaningful updates in the last 30 days and carries a velocity score of 0.0 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About spEDM
Spatial causal discovery in R, one exposed method per release
spEDM brings empirical dynamic modeling to spatial data — cross mapping, convergent cross mapping and pattern causality over spatial vector and raster inputs, with the numerics in C++ behind S4 generics. The recent releases have exposed geographical pattern causality and spatially convergent partial cross mapping at the R level with vignettes, and 1.12 turns to consolidating the API. It is part of the stscl family alongside the temporal-domain tEDM, with which it shares both its C++ core and its maintainer.
Velocity 0.0 · Last update 45m ago
Top 12 alternatives to spEDM
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
gcube's recent releases are all packaging metadata, not simulation code
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The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
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ggstats keeps widening what a coefficient or Likert plot can be
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ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
ANALYTICS
State-space data simulation for R, filled in one function at a time
ANALYTICS
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
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A ggplot2 inset-map extension that is now infrastructure for other packages
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hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems
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NSW boundary data for R, refreshed as the official sources move
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Biodiversity impact indicators settle their vocabulary before 1.0
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A dormant trajectory-inference wrapper wakes up for maintenance only
spEDM vs alternatives — shipping velocity at a glance
Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.
| Product | Velocity | Sparks · 30d | Focus areas | Latest release |
|---|---|---|---|---|
| spEDM (baseline) | 0.0 | 0 | causal-inferencespatial-analysisempirical-dynamic-modeling | — |
| fillpattern | 0.0 | 0 | ggplot2data-visualizationaccessibility | — |
| gcube | 0.0 | 0 | biodiversitysimulationoccurrence-cubes | — |
| cubist | 0.0 | 0 | machine-learningrule-based-modelstidymodels | — |
| ggstats | 0.0 | 0 | ggplot2data-visualizationlikert | — |
| ecodive | 0.0 | 0 | microbiomeecologydiversity-metrics | 2.0.0 expands to ~14 alpha and ~30 beta diversity metrics |
| simStateSpace | 0.0 | 0 | state-space-modelssimulationlongitudinal-data | — |
| rollama | 0.0 | 0 | local-llmollamatext-annotation | rollama 0.3.0 adds logprobs, caching and batched queries |
| ggmapinset | 0.0 | 0 | ggplot2geospatialinset-maps | — |
| hoopr | 0.0 | 0 | sports-databasketballapi-client | hoopR 3.0.0 moves every API backend to httr2 |
| nswgeo | 0.0 | 0 | geospatialaustraliapublic-health | — |
| impIndicator | 0.0 | 0 | biodiversityinvasive-speciesoccurrence-cubes | — |
| dynwrap | 0.0 | 0 | single-celltrajectory-inferencebioinformatics | — |
The 12 best spEDM alternatives, in depth
1. fillpattern · velocity 0.0
Pattern fills for ggplot2, hardened against the ways users write sizes.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, fillpattern focuses on ggplot2, data visualization and accessibility.
fillpattern and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full fillpattern trajectory → · Compare spEDM vs fillpattern →
2. gcube · velocity 0.0
Gcube's recent releases are all packaging metadata, not simulation code.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, gcube focuses on biodiversity, simulation and occurrence cubes.
gcube and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
3. cubist · velocity 0.0
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, cubist focuses on machine learning, rule based models and tidymodels.
cubist and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
4. ggstats · velocity 0.0
Ggstats keeps widening what a coefficient or Likert plot can be.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, ggstats focuses on ggplot2, data visualization and likert.
ggstats and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
5. ecodive · velocity 0.0
Ecodive rebuilt itself into a broad diversity-metric library, breaking as it went.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “2.0.0 expands to ~14 alpha and ~30 beta diversity metrics”.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, ecodive focuses on microbiome, ecology and diversity metrics.
ecodive and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
6. simStateSpace · velocity 0.0
State-space data simulation for R, filled in one function at a time.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, simStateSpace focuses on state space models, simulation and longitudinal data.
simStateSpace and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full simStateSpace trajectory → · Compare spEDM vs simStateSpace →
7. rollama · velocity 0.0
Rollama turns a local-LLM wrapper into an instrument for reproducible annotation.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “rollama 0.3.0 adds logprobs, caching and batched queries”.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, rollama focuses on local llm, ollama and text annotation.
rollama and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
8. ggmapinset · velocity 0.0
A ggplot2 inset-map extension that is now infrastructure for other packages.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, ggmapinset focuses on ggplot2, geospatial and inset maps.
ggmapinset and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full ggmapinset trajectory → · Compare spEDM vs ggmapinset →
9. hoopr · velocity 0.0
HoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “hoopR 3.0.0 moves every API backend to httr2”.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, hoopr focuses on sports data, basketball and api client.
hoopr and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
10. nswgeo · velocity 0.0
NSW boundary data for R, refreshed as the official sources move.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, nswgeo focuses on geospatial, australia and public health.
nswgeo and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
11. impIndicator · velocity 0.0
Biodiversity impact indicators settle their vocabulary before 1.0.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, impIndicator focuses on biodiversity, invasive species and occurrence cubes.
impIndicator and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full impIndicator trajectory → · Compare spEDM vs impIndicator →
12. dynwrap · velocity 0.0
A dormant trajectory-inference wrapper wakes up for maintenance only.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where spEDM leans on causal inference, spatial analysis and empirical dynamic modeling, dynwrap focuses on single cell, trajectory inference and bioinformatics.
dynwrap and spEDM have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Frequently asked questions
What are the best alternatives to spEDM?
The top spEDM alternatives we currently track in analytics tools are fillpattern, gcube, cubist, ggstats, ecodive, ranked by recent ship velocity.
How is this list of spEDM alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare spEDM directly with one of these alternatives?
Yes — every card has a "Compare with spEDM" link to a side-by-side /compare page.