runs a dataset through a previously estimated DFM to obtain predictions for all missing values in the series.
predict_dfm(data, output_dfm, months_ahead = 3, lag = 0)matrix of variables, size (n_obs, n_variables). Must include in 1st column a series of type date, called "date", all data already stationary.
list, the output of the dfm() function.
number of months ahead to forecast.
number of lags for the kalman filter
dataframe with all missing values filled + predictions.