predict_dfm: Predictions from an estimated dynamic factor model.

In dhopp1/nowcastDFM: DFMs for Nowcasting

Predictions from an estimated dynamic factor model.

Description

runs a dataset through a previously estimated DFM to obtain predictions for all missing values in the series.

Usage

predict_dfm(data, output_dfm, months_ahead = 3, lag = 0)

Arguments

data	matrix of variables, size (n_obs, n_variables). Must include in 1st column a series of type date, called "date", all data already stationary.
output_dfm	list, the output of the dfm() function.
months_ahead	number of months ahead to forecast.
lag	number of lags for the kalman filter

Value

dataframe with all missing values filled + predictions.

dhopp1/nowcastDFM documentation built on May 27, 2023, 4:03 a.m.