Package index • echos

Base functions

Functions and methods for basic time series forecasting

train_esn(): Train an Echo State Network
forecast_esn(): Forecast an Echo State Network
tune_esn(): Tune hyperparameters of an Echo State Network
print(<esn>): Print model specification of the trained ESN model
summary(<esn>): Provide a detailed summary of the trained ESN model
summary(<tune_esn>): Provide a summary of the hyperparameter tuning
is.esn(): Checks if object is of class "esn"
is.forecast_esn(): Checks if object is of class "forecast_esn"
is.tune_esn(): Checks if object is of class "tune_esn"
plot(<esn>): Plot internal states of a trained ESN model
plot(<forecast_esn>): Plot forecasts of a trained ESN model
plot(<tune_esn>): Plot forecasts from a tuned ESN object
run_reservoir: Run reservoir

Tidy functions

Functions and methods in tidy time series forecasting (“fable framework”)

ESN(): Train an Echo State Network
forecast(<ESN>): Forecast an Echo State Network
fitted(<ESN>): Extract fitted values from a trained ESN
residuals(<ESN>): Extract residuals from a trained ESN
model_sum(<ESN>): Model specification of a trained ESN model
tidy(<ESN>): Estimated coefficients
glance(<ESN>): Summary of trained models during random search
report(<ESN>): Provide a detailed summary of the trained ESN model
filter_esn(): Filter ESN models
reservoir(): Return the reservoir from a trained ESN as tibble

Datasets

Datasets

m4_data: M4 dataset
synthetic_data: Synthetic data