predict.factors: Make predictions from a '"factors"' object

In HDTSA: High Dimensional Time Series Analysis Tools

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 "factors" constructed by Factors.
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 auto.arima() of forecast. See 'Details' and the manual of auto.arima(). The default is list(ic = "aic").
control_VAR	A list of arguments passed to the function VAR() of vars. See 'Details' and the manual of VAR(). The default is list(type = "const", lag.max = 6, ic = "AIC").
...	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

Factors

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)

HDTSA documentation built on April 3, 2025, 11:07 p.m.