Artifacts using Qgraph (18)

Estimation of k-Order time-varying Mixed Graphical Models and mixed VAR(p) models via elastic-net regularized neighborhood regression. For details see linked paper.

Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / eBIC) or crossvalidation.

Automated identification and estimation of group- and individual-level relations in time series data from within a structural equation modeling framework.

Estimates within and between time point interactions in experience sampling data, using the Graphical VAR model in combination with LASSO and EBIC.

A pure data-driven gene network, weighted gene co-expression network (WGCN) could be constructed only from expression profile. Different layers in such networks may represent different time points, multiple conditions or various species. AMOUNTAIN aims to search active modules in multi-layer WGCN using a continuous optimization approach.