backtest: Backtesting of a scalar ARIMA model
In d-/MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

backtest

R Documentation

Backtesting of a scalar ARIMA model

Perform out-of-sample prediction of a given ARIMA model and compute the summary statistics

backtest(m1, rt, orig, h = 1, xre = NULL, fixed = NULL, 
  inc.mean = TRUE, reest = 1, method = c("CSS-ML"))

`m1`	An output of the arima command for scalar time series
`rt`	The time series under consideration
`orig`	The starting forecast origin. It should be less than the length of the underlying time series
`h`	The forecast horizon. For a given h, it computes 1-step to h-step ahead forecasts
`inc.mean`	A logical switch. It is true if mean vector is estimated.
`fixed`	A vector of the length of the number of coefficients of the ARIMA model. It is used in R for parameter constraint.
`xre`	A matrix containing the exogeneous variables used in the ARIMA model
`reest`	A control variable used to re-fit the model in prediction. The program will re-estimate the model for every new reest observations. The default is 1. That is, re-estimate the model with every new data point.
`method`	Estimation method in the ARIMA model

Perform estimation-prediction-reestimation in the forecasting subsample, and to compuate the summary statistics

`origion`	Forecast origin
`error`	forecast errors
`forecasts`	forecasts
`rmse`	Root mean squared forecast errors
`mabso`	Mean absolute forecast errors
`reest`	Return the reest value