Package: echos 1.0.5

Alexander Häußer

echos: Echo State Networks for Time Series Modeling and Forecasting

Provides a lightweight implementation of functions and methods for fast and fully automatic time series modeling and forecasting using Echo State Networks (ESNs).

Authors:Alexander Häußer [aut, cre, cph]

echos_1.0.5.tar.gz
echos_1.0.5.zip(r-4.7-x86_64)echos_1.0.5.zip(r-4.7-arm64)echos_1.0.5.zip(r-4.6-x86_64)echos_1.0.5.zip(r-4.6-arm64)
echos_1.0.5.tar.gz(r-4.7-arm64)echos_1.0.5.tar.gz(r-4.7-x86_64)echos_1.0.5.tar.gz(r-4.6-arm64)echos_1.0.5.tar.gz(r-4.6-x86_64)
echos_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
echos/json (API)

# Install 'echos' in R:
install.packages('echos', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ahaeusser/echos/issues

Pkgdown/docs site:https://ahaeusser.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

4.24 score 1 stars 29 scripts 512 downloads 10 exports 42 dependencies

Last updated from:df805e13c6. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK173
linux-devel-x86_64OK212
source / vignettesOK256
linux-release-arm64OK157
linux-release-x86_64OK193
windows-devel-arm64OK272
windows-devel-x86_64OK158
windows-release-arm64OK303
windows-release-x86_64OK164
wasm-releaseOK113

Exports:ESNfilter_esnforecast_esnis.esnis.forecast_esnis.tune_esnreservoirrun_reservoirtrain_esntune_esn

Dependencies:anytimeBHclicpp11distributionaldplyrfabletoolsfarvergenericsggdistggplot2gluegtableisobandlabelinglifecyclelubridatemagrittrnumDerivpillarpkgconfigprogressrpurrrquadprogR6RColorBrewerRcppRcppArmadillorlangS7scalesstringistringrtibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewithr

Base functions
Load package | Prepare dataset | ESN architecture and automatic model selection | Train ESN model | Forecast ESN model | Hyperparameter tuning
Rendered fromvignette_100_base_airpassengers.Rmdusingknitr::rmarkdown

Last update: 2026-10-22
Started: 2026-10-22

Datasets
Introduction | Load packages | M4 data | Synthetic data
Rendered fromvignette_300_datasets.Rmdusingknitr::rmarkdown

Last update: 2026-10-22
Started: 2026-10-22

Multiple models
Load package | Prepare dataset | Train ESN model | Forecast ESN model
Rendered fromvignette_201_tidy_m4_monthly_models.Rmdusingknitr::rmarkdown

Last update: 2026-10-22
Started: 2026-10-22

Rolling forecasts
Introduction | Load packages | Prepare the data | Define the rolling forecast setup | Create rolling training windows | Train the ESN models | Generate rolling forecasts | Evaluate forecast accuracy | Visualize the rolling forecasts | Summary
Rendered fromvignette_202_tidy_m4_monthly_splits.Rmdusingknitr::rmarkdown

Last update: 2026-10-22
Started: 2026-10-22