R: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

# Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

## Documentation for package ‘fnets’ version 0.1.6

- DESCRIPTION file
- Package README

## Help Pages

data.restricted | Simulated data from the restricted factor-adjusted vector autoregression model
data.unrestricted | Simulated data from the unrestricted factor-adjusted vector autoregression model
factor.number | Factor number selection methods
fnets | Factor-adjusted network estimation
fnets.factor.model | Factor model estimation
fnets.var | 'l1'-regularised Yule-Walker estimation for VAR processes
network | Convert networks into igraph objects
network.fnets | Convert networks estimated by fnets into igraph objects
par.lrpc | Parametric estimation of long-run partial correlations of factor-adjusted VAR processes
plot.factor.number | Plot factor number
plot.fnets | Plotting the networks estimated by fnets
plot.threshold | Plotting the thresholding procedure
predict.fm | Forecasting for factor models
predict.fnets | Forecasting by fnets
print.factor.number | Print factor number
print.fm | Print factor model
print.fnets | Print fnets
print.threshold | Print threshold
sim.restricted | Simulate data from a restricted factor model
sim.unrestricted | Simulate data from an unrestricted factor model
sim.var | Simulate a VAR(1) process
threshold | Threshold the entries of the input matrix at a data-driven level