# Dynamic Factor Models

## Documentation for package ‘dfms’ version 0.3.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

dfms-package | Dynamic Factor Models
.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
coef.dfm | DFM Summary Methods
DFM | Estimate a Dynamic Factor Model
dfms | Dynamic Factor Models
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)
logLik.dfm | DFM Summary Methods
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