predict.factors {HDTSA} | R Documentation |
Make predictions from a "factors"
object
Description
This function makes predictions from a "factors"
object.
Usage
## S3 method for class 'factors'
predict(
object,
newdata = NULL,
n.ahead = 10,
control_ARIMA = list(),
control_VAR = list(),
...
)
Arguments
object |
An object of class |
newdata |
Optional. A new data matrix to predict from. |
n.ahead |
An integer specifying the number of steps ahead for prediction. |
control_ARIMA |
A list of arguments passed to the function
|
control_VAR |
A list of arguments passed to the function
|
... |
Currently not used. |
Details
Forecasting for {\bf y}_t
can be implemented in two steps:
Step 1. Get the h
-step ahead forecast of the \hat{r} \times 1
time series \hat{\bf x}_t
[See Factors
], denoted by
\hat{\bf x}_{n+h}
, using a VAR model
(if \hat{r} > 1
) or an ARIMA model (if \hat{r} = 1
). The orders
of VAR and ARIMA models are determined by AIC by default. Otherwise, they
can also be specified by users through the arguments control_VAR
and control_ARIMA
, respectively.
Step 2. The forecasted value for {\bf y}_t
is obtained by
\hat{\bf y}_{n+h}= \hat{\bf A}\hat{\bf x}_{n+h}
.
Value
ts_pred |
A matrix of predicted values. |
See Also
Examples
library(HDTSA)
data(FamaFrench, package = "HDTSA")
## Remove the market effects
reg <- lm(as.matrix(FamaFrench[, -c(1:2)]) ~ as.matrix(FamaFrench$MKT.RF))
Y_2d = reg$residuals
res_factors <- Factors(Y_2d, lag.k = 5)
pred_fac_Y <- predict(res_factors, n.ahead = 1)