predict.sparseDFM {sparseDFM}

Forecasting factor estimates and data series.

Description

Predict the next h steps ahead for the factor estimates and the data series. Given information up to time t, a h-step ahead forecast is \bm{X}_{t+h}=\bm{\Lambda}\bm{A}^{h}\bm{F}_t+\bm{\Phi}^h\bm{\epsilon}_t, where \bm{\Phi}=0 for the IID idiosyncratic error case.

Usage

## S3 method for class 'sparseDFM'
predict(object, h = 1, standardize = FALSE, alpha_index = "best", ...)

## S3 method for class 'sparseDFM_forecast'
print(x, ...)

Arguments

object

an object of class 'sparseDFM'.

h

integer. The number of steps ahead to compute the forecast for. Default is h=1.

standardize

logical. Returns data series forecasts in the original data scale if set to FALSE. Default is FALSE.

alpha_index

Choose which L1 penalty parameter to display the results for. Default is 'best'. Otherwise, input a number between 1:length(alpha_grid) that indicates the required alpha parameter.

...

Further print arguments.

x

an object of class 'sparseDFM_forecast' from predict.sparseDFM.

Value

X_hat h \times p numeric matrix of data series forecasts.

F_hat h \times r numeric matrix of factor forecasts.

e_hat h \times p numeric matrix of AR(1) idiosyncratic error forecasts if err=AR1 in sparseDFM.

h forecasts produced for h steps ahead.

err the type of idiosyncratic errors used in sparseDFM.

Prints out the h-step ahead forecast from predict.sparseDFM.