Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series
Information criterion for factor-adjusted VAR estimation
Factor number estimator of Alessi, Barigozzi and Capasso (2010)
Bartlett weights
Blockwise VAR estimation under GDFM
Forecasting the factor-driven common component
Dynamic PCA
extended Bayesian Information Criterion
full likelihood
Factor number selection methods
Factor model estimation
Factor-adjusted network estimation
internal function for fnets.var
l1-regularised Yule-Walker estimation for VAR processes
Factor number estimator of Hallin and Liška (2007)
Forecasting idiosyncratic VAR process
logarithmic factorial of n
Convert networks estimated by fnets into igraph objects
Convert networks into igraph objects
Parametric estimation of long-run partial correlations of factor-adjus...
Plot factor number
Plotting the networks estimated by fnets
Plotting the thresholding procedure
internal function for plot.fnets and network
Forecasting for factor models
Forecasting by fnets
Print factor number
Print factor model
Print fnets
Print threshold
Simulate data from a restricted factor model
Simulate data from an unrestricted factor model
Simulate a VAR(1) process
Static PCA
Threshold the entries of the input matrix at a data-driven level
Plotting output for tuning parameter selection in fnets
Dantzig selector-type estimator of VAR processes via constrained l1-...
Lasso-type estimator of VAR processes via l1-regularised M-estimat...
Cross validation for factor-adjusted VAR estimation
Implements methods for network estimation and forecasting of high-dimensional time series exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model. See Barigozzi, Cho and Owens (2024+) <doi:10.1080/07350015.2023.2257270> for further descriptions of FNETS methodology and Owens, Cho and Barigozzi (2024+) <arXiv:2301.11675> accompanying the R package.