The most commonly used R-packages for estimating psychological networks at present are listed below. Many of these are under development, and it is advised to make sure to always install the most recent versions of the packages from the authors’ Github pages via the devtools package.

*qgraph*| A great package to visualize all kinds of different networks; includes many network estimation routines in cross-sectional data.*IsingFit*| For estimating*Ising Models*in cross-sectional data (networks with binary variables). Related, the*IsingSampler*package allows you to simulate data from Ising Models.*mgm*| For estimating*Mixed Graphical Models*in cross-sectional data, and time-varying time-series networks models (i.e. network models that can change over time).*bootnet*| A hub package that, among others, allows for estimating all sorts of cross-sectional network models via the ‘default’ argument (including GGM, Ising Model, MGM, regularized, nonregularized, and many more; see here for a recent overview). Importantly, the package also estimates the accuracy and stability of network models via boostrapping routines.*NetworkComparisonTest*| For testing the difference of network structures across different samples, and across the same sample over time.*NetworkTools*| For estimating bridge centrality, detecting redundant nodes with goldbricker, and for plotting networks with multidimensional scaling, PCA, or eigenmodels.*graphicalVAR*| For estimating time-series network models (vector autoregression models; VAR) in case of n=1.*mlVAR*| For estimating time-series network models (multilevel vector autoregression models; multilevel VAR) in case of n>1.*GIMME*| gimme (Group Iterative Multiple Model Estimation) is the automated identification and estimation of group- and individual-level relations in time series data from within a structural equation modeling framework. Tackles similar data to*mlVAR*, but has a different estimation routine.*NetworkToolbox*| I haven’t played around with this yet, the CRAN description is “NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis”.*iqgraph*| Very well established and powerful tool from social network analysis.*BGGM*| A new package on Bayesian Gaussian Graphical Models.*GGMnonreg*| Estimation of nonregularized Gaussian Graphical Models.*EGA*| Exploratory Graph Analysis allows you to determine the optimal number of communities in a network structures via the walktrap algorithm.*lvnet*| The Latent Variable Network Modeling is a package that simultaneously estimates factor and network models, which can be useful when you want to estimate e.g. a network of factor scores.