mgm: Structure Estimation for Time-Varying Mixed Graphical Models in high-dimensional Data
Jonas M B Haslbeck, Lourens Waldorp · UvA-DARE (University of Amsterdam) · 2015
We present the R-package mgm for the estimation of both stationary and time-varying Mixed Graphical Models and mixed Vector Autoregressive models in high-dimensional data. These are a useful extensions of graphical models for only one variable type, since mixed types of variables (continuous, count, categorical) are ubiquitous in datasets in many disciplines. In addition, we extend both models to the time-varying case in which the true model changes over time under the assumption that change is a smooth function of time. Time-varying models offer a rich description of temporally evolving systems as they provide information about organizational processes, information diffusion, vulnerabilities, and the potential impact of interventions. Next to providing the background of the implemented methods, we provide a number of fully reproducible code examples that illustrate how to use the software package.