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Comparison · Infra & APIs

echos vs inlabru

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

echos vs inlabru: at a glance

Featureechosinlabru
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themestime-series, forecasting, reservoir-computing, hyperparameter-tuningbayesian-modelling, spatial-statistics, r-package, api-consolidation
Last editorial update1h ago38m ago
WebsiteVisit →Visit →

What is echos?

Echo state networks for R forecasting, filling in the pieces a fable model is expected to have.

echos fits echo state networks, a reservoir-computing approach to time series forecasting, and exposes them through the fabletools model interface so they sit alongside other models in a fable workflow. The three releases in this window take it from a working model to a complete one: forecast intervals in 1.0.2, hyperparameter tuning by rolling-origin cross-validation in 1.0.3, and documentation covering the architecture, hyperparameters and tuning workflow in 1.0.4. Cadence is a few releases a year.

Read the full echos trajectory →

What is inlabru?

A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time

inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.

Read the full inlabru trajectory →

echos vs inlabru: editorial side-by-side

E
echos
INFRA · APIS
0.0

Echo state networks for R forecasting, filling in the pieces a fable model is expected to have.

◆ Current state

echos fits echo state networks, a reservoir-computing approach to time series forecasting, and exposes them through the fabletools model interface so they sit alongside other models in a fable workflow. The three releases in this window take it from a working model to a complete one: forecast intervals in 1.0.2, hyperparameter tuning by rolling-origin cross-validation in 1.0.3, and documentation covering the architecture, hyperparameters and tuning workflow in 1.0.4. Cadence is a few releases a year.

◆ Where it's heading

The arc here is a model implementation earning its place in an established framework. Point forecasts came first, then the interval forecasts that any fable-compatible model is expected to produce, generated by bootstrapping residuals and taking quantiles from simulated paths, then the tuning machinery that makes the reservoir hyperparameters usable by people who do not already know what alpha and rho do. Version 1.0.4 spending its whole release on documentation and a clearer dataset name is consistent with that: the remaining barrier is comprehension, not capability.

◆ Prediction

With intervals and tuning in place, the natural next step is broader integration with the fable ecosystem, such as handling multiple series or ensembling with other model types. The entries do not indicate whether the maintainer intends to go further into reservoir variants or to stabilise what is here.

I
inlabru
INFRA · APIS
2.5

A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time

◆ Current state

inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.

◆ Where it's heading

The arc is consolidation of the extension surface rather than expansion of the model catalogue. Every release adds mappers or families with one hand and removes a dependency, a re-export or a deprecated path with the other — plyr in 2.15.0, fmesher's Depends entry in 2.14.1, sp and ggmap in 2.12.0. The compatibility flag bru_compat_pre_2_14_enable and the temporary fm_int/fm_pixels re-exports show a maintainer sequencing breaks across releases instead of landing them together.

◆ Prediction

The 2.14 compatibility flag is still defaulting to TRUE and the fmesher re-exports are described in the entries as temporary, so the next obvious move is a release that flips bru_compat_pre_2_14_enable off and drops those re-exports.

Alternatives to echos and inlabru

Other Infra & APIs 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 echos or inlabru.

See all echos alternatives → · See all inlabru alternatives →

Recent activity from echos and inlabru

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

  1. 23d agoinlabruPredictor linearisation rewritten; broom tidiers, truncated families
  2. 2mo agoechosDocumentation expanded; M4 dataset renamed
  3. 3mo agoinlabruBugfix release: factor contrasts, raster extraction, error classes
  4. 5mo agoinlabruNew mappers, standardised cgeneric support, bru_obs storage refactor
  5. 5mo agoechostune_esn() tunes reservoir hyperparameters by cross-validation
  6. 1y agoinlabruMapper classes shortened to bm_*, experimental predictor aggregation
  7. 1y agoechosForecast intervals added via moving block bootstrap
  8. 1y agoinlabruDrops sp and ggmap for an sf-native spatial stack

Frequently asked questions

What is the difference between echos and inlabru?

They serve adjacent needs but don't currently overlap on shipped themes. inlabru 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 echos better than inlabru?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. inlabru 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to echos?

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

What are the best alternatives to inlabru?

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