predict.tenAR {tensorTS} | R Documentation |
Predict funcions for Tensor Autoregressive Models
Description
S3 method for the 'tenAR' class using the generic predict function. Prediction based on the tensor autoregressive model or reduced rank MAR(1) model. If rolling = TRUE
, returns the rolling forecasts.
Usage
## S3 method for class 'tenAR'
predict(object, n.ahead = 1, xx = NULL, rolling = FALSE, n0 = NULL, ...)
Arguments
object |
a model object returned by |
n.ahead |
prediction horizon. |
xx |
|
rolling |
TRUE or FALSE, rolling forecast, is FALSE by default. |
n0 |
only if |
... |
Additional arguments passed to the method. |
Value
a tensor time series of length n.ahead
if rolling = FALSE
;
a tensor time series of length T^{\prime} - n_0 - n.ahead + 1
if rolling = TRUE
.
See Also
'predict.ar' or 'predict.arima'
Examples
set.seed(333)
dim <- c(2,2,2)
t = 20
xx <- tenAR.sim(t, dim, R=2, P=1, rho=0.5, cov='iid')
est <- tenAR.est(xx, R=1, P=1, method="LSE")
pred <- predict(est, n.ahead = 1)
# rolling forcast
n0 = t - min(50,t/2)
pred.rolling <- predict(est, n.ahead = 5, xx = xx, rolling=TRUE, n0)
# prediction for reduced rank MAR(1) model
dim <- c(2,2)
t = 20
xx <- tenAR.sim(t, dim, R=1, P=1, rho=0.5, cov='iid')
est <- matAR.RR.est(xx, method="RRLSE", k1=1, k2=1)
pred <- predict(est, n.ahead = 1)
# rolling forcast
n0 = t - min(50,t/2)
pred.rolling <- predict(est, n.ahead = 5, rolling=TRUE, n0=n0)
[Package tensorTS version 1.0.2 Index]