nmfkc.ar.predict computes multi-step-ahead forecasts for a fitted NMF-VAR model
using recursive forecasting.
If the fitted model contains time series property information (from nmfkc.ar),
the forecasted values will have appropriate time-based column names.
nmfkc.ar.predict(x, Y, degree = NULL, n.ahead = 1)An object of class nmfkc (the fitted model).
The historical observation matrix used for fitting (or at least the last degree columns).
Optional integer. Lag order (D). If NULL (default), it is inferred
from x$A.attr (when available) or from the dimensions of x$C.
Integer (>=1). Number of steps ahead to forecast.
A list with components:
A \(P \times n.ahead\) matrix of predicted values. Column names are future time points if time information is available.
A numeric vector of future time points corresponding to the columns of pred.