forecast_esn: Forecast an Echo State Network

In ahaeusser/echos: Echo State Networks for Time Series Modeling and Forecasting

Forecast an Echo State Network

Description

Forecast an Echo State Network (ESN) from a trained model via recursive forecasting.

Usage

forecast_esn(
  object,
  n_ahead = 18,
  levels = c(80, 95),
  n_sim = 100,
  n_seed = 42
)

Arguments

object	An object of class esn. The result of a call to train_esn().
n_ahead	Integer value. The number of periods for forecasting (i.e. forecast horizon).
levels	Integer vector. The levels of the forecast intervals, e.g., 80% and 95%.
n_sim	Integer value. The number of future sample path generated during simulation.
n_seed	Integer value. The seed for the random number generator (for reproducibility).

Value

A list containing:

• point: Numeric vector containing the point forecasts.

• interval: Numeric matrix containing the forecast intervals.

• sim: Numeric matrix containing the simulated future sample path.

• levels: Integer vector. The levels of the forecast intervals.

• actual: Numeric vector containing the actual values.

• fitted: Numeric vector containing the fitted values.

• n_ahead: Integer value. The number of periods for forecasting (forecast horizon).

• model_spec: Character value. The model specification as string.

Examples

xdata <- as.numeric(AirPassengers)
xmodel <- train_esn(y = xdata)
xfcst <- forecast_esn(xmodel, n_ahead = 12)
plot(xfcst)

ahaeusser/echos documentation built on June 2, 2025, 2:17 a.m.