| SWfore {MTS} | R Documentation |
Stock-Watson Diffusion Index Forecasts
Description
Uses the diffusion index approach of Stock and Watson to compute out-of-sample forecasts
Usage
SWfore(y, x, orig, m)
Arguments
y |
The scalar variable of interest |
x |
The data matrix (T-by-k) of the observed explanatory variables |
orig |
Forecast origin |
m |
The number of diffusion index used |
Details
Performs PCA on X at the forecast origin. Then, fit a linear regression model to obtain the coefficients of prediction equation. Use the prediction equation to produce forecasts and compute forecast errors, if any. No recursive estimation is used.
Value
coef |
Regression coefficients of the prediction equation |
yhat |
Predictions at the forecast origin |
MSE |
Mean squared errors, if available |
loadings |
Loading matrix |
DFindex |
Diffusion indices |
Author(s)
Ruey S. Tsay
References
Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.