Dynamic Factor Models


[Up] [Top]

Documentation for package ‘dfms’ version 0.2.2

Help Pages

.VAR (Fast) Barebones Vector-Autoregression
ainv Armadillo's Inverse Functions
apinv Armadillo's Inverse Functions
as.data.frame.dfm Extract Factor Estimates in a Data Frame
as.data.frame.dfm_forecast DFM Forecasts
BM14_M Euro Area Macroeconomic Data from Banbura and Modugno 2014
BM14_Models Euro Area Macroeconomic Data from Banbura and Modugno 2014
BM14_Q Euro Area Macroeconomic Data from Banbura and Modugno 2014
DFM Estimate a Dynamic Factor Model
em_converged Convergence Test for EM-Algorithm
FIS (Fast) Fixed-Interval Smoother (Kalman Smoother)
fitted.dfm DFM Residuals and Fitted Values
ICr Information Criteria to Determine the Number of Factors (r)
plot.dfm Plot DFM
plot.dfm_forecast DFM Forecasts
plot.ICr Information Criteria to Determine the Number of Factors (r)
predict.dfm DFM Forecasts
print.dfm DFM Summary Methods
print.dfm_forecast DFM Forecasts
print.dfm_summary DFM Summary Methods
print.ICr Information Criteria to Determine the Number of Factors (r)
resid.dfm DFM Residuals and Fitted Values
residuals.dfm DFM Residuals and Fitted Values
screeplot.dfm Plot DFM
screeplot.ICr Information Criteria to Determine the Number of Factors (r)
SKF (Fast) Stationary Kalman Filter
SKFS (Fast) Stationary Kalman Filter and Smoother
summary.dfm DFM Summary Methods
tsnarmimp Remove and Impute Missing Values in a Multivariate Time Series