Description | Features | Getting Started | Installation | Documentation | Fitting JANE on networks without noise edges | Available models | model = "NDH" | model = "RS" | model = "RSR" | Fitting JANE on networks with noise edges | family = "poisson" | family = "lognormal" | family = "bernoulli" (default) | guess_noise_weights | Simulating networks | Model selection criteria for choosing the number of clusters | Initialization of EM algorithm | Specification of prior hyperparameters | Prior distributions | Prior on $\boldsymbol{\mu}_k$ and $\boldsymbol{\Omega}_k$ | Prior on $\boldsymbol{p}$ | Prior on $\boldsymbol{\beta}_{LR}$ | Prior on $q$ | Zero-truncated Poisson | Prior on $\boldsymbol{\beta}_{GLM}$ | Log-normal | Prior on $\tau^2_{\text{weights}}$ | Prior on $\tau^2_{\text{noise weights}}$ | Default hyperparameters | Example of specifying hyperparameters for a single combination of $K$ and $D$ | Example of specifying hyperparameters for multiple combinations of $K$ and $D$ | Nested list | Unevaluated calls | Parallel implementation of JANE() | Case-control implementation of JANE() | Using S3 methods with JANE objects | print() | summary() | plot() | Latent space clustering (default type = "lsnc") | Misclassified actors (type = "misclassified") | Clustering uncertainty (type = "uncertainty") | EM trace plot (type = "trace_plot") | Additional options | References