Predict method for objects of class ‘VAR’, ‘VECM’ or ‘TVAR’
Forecating the level of a series estimated by ‘VAR’ / ‘VECM’ or ‘TVAR’
## S3 method for class 'TVAR' predict(object, newdata, n.ahead = 5, newdataTrendStart, ...) ## S3 method for class 'VAR' predict(object, newdata, n.ahead = 5, newdataTrendStart, exoPred = NULL, ...)
object |
An object of class ‘ |
newdata |
Optional. A new data frame to predict from. This should contain lags of the level of the original series. See Details. |
n.ahead |
An integer specifying the number of forecast steps. |
newdataTrendStart |
If ‘ |
... |
Arguments passed to the unexported ‘ |
exoPred |
vector/matrix of predictions for the exogeneous variable(s) (with ‘ |
The forecasts are obtained recursively, and are for the levels of the series.
When providing newdata, newdata has to be ordered chronologically, so that the first row/element is the earliest value.
For VECM, the forecasts are obtained by transforming the VECM to a VAR (using function VARrep).
Note that a VECM(lag=p) corresponds to a VAR(lag=p+1), so that if the user provides newdata
for a VECM(lag=p), newdata should actually contain p+1 rows.
A matrix of predicted values.
Matthieu Stigler
A more sophisticated predict function, allowing to do sub-sample rolling
predictions: predict_rolling.
data(barry)
barry_in <- head(barry, -5)
barry_out <- tail(barry, 5)
mod_vecm <- VECM(barry_in, lag=2)
mod_var <- lineVar(barry_in, lag=3)
mod_tvar <- TVAR(barry_in, lag=3, nthresh=1, thDelay=1)
pred_vecm <- predict(mod_vecm)
pred_var <- predict(mod_var)
pred_tvar <- predict(mod_tvar)
## compare forecasts on a plot
n <- 30
plot(1:n, tail(barry[,1], n), type="l", xlim=c(0,n))
lines((n-5+1):n, pred_var[,1], lty=2, col=2)
lines((n-5+1):n, pred_vecm[,1], lty=2, col=3)
lines((n-5+1):n, pred_tvar[,1], lty=2, col=4)
legend("bottomright", lty=c(1,2,2,2), col=1:4, legend=c("true", "var", "vecm", "tvar"))
## example for newdata:
all.equal(predict(mod_vecm), predict(mod_vecm, newdata=barry[c(317, 318, 319),]))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.