fp.forecast: Do automatic Box-Jenkins ARIMA fit and forecast.

In forecastLSW: Forecasting Routines for Locally Stationary Wavelet Processes

Do automatic Box-Jenkins ARIMA fit and forecast.

Description

This function merely wraps some excellent functions from the forecast package up and returns the forecast values and their lower and upper prediction intervals.

Usage

fp.forecast(x, h = 1, conf.level = 95)

Arguments

x	The time series you wish to forecast.
h	The number of steps ahead (forecast horizon)
conf.level	The confidence level for the forecast prediction interval expressed as a value between 0 and 100.

Details

This function entirely relies on existing functions from the forecast package. It applies auto.arima to x to fit an ARIMA model to the series with an automatic choice of parameters. Then the forecast function is applied to the ARIMA object to obtain forecasts and prediction intervals.

Value

A matrix with h rows and three columns. The first column contains the forecasted values. The second and third columns contrain the lower and upper prediction intervals.

Author(s)

G.P. Nason

References

Killick, R., Knight, M.I., Nason, G.P., Nunes M.A., Eckley I.A. (2023) Automatic Locally Stationary Time Series Forecasting with application to predicting U.K. Gross Value Added Time Series under sudden shocks caused by the COVID pandemic arXiv:2303.07772

Hyndman, R.J. and Khandakar, Y. (2008) Automatic Time Series Forecasting: The forecast package for R. Journal of Statistical Software, 27, Issue 3.

Examples

#
# Generate random test series
#
x.test <- tvar2sim()
#
# Produce stationary Box-Jenkins forecasts and prediction intervals for
# two-steps ahead
#
fp.forecast(x.test, h=2)

forecastLSW documentation built on Aug. 22, 2025, 1:09 a.m.