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Shows side-by-side heatmaps of the true adjacency matrix, PIP, and thresholded estimate. Returns confusion metrics invisibly.

Usage

plot_recovery(fit, true_adj, pip_threshold = 0.5, groups = NULL)

Arguments

fit

A multiggm_fit object returned by multiggm_mcmc.

true_adj

A list of K true adjacency matrices (0/1), or a single matrix (recycled for all groups).

pip_threshold

Numeric; threshold for edge selection. Default 0.5.

groups

Integer vector; which groups to plot. Default: all groups.

Value

A named list of confusion metric vectors per group (invisible). Each element is a named numeric vector as returned by confusion_at_threshold, with components TP, FP, TN, FN, TPR, FPR.

Examples

sim <- simulate_multiggm(K = 2, p = 8, n = 80, seed = 1)
fit <- multiggm_mcmc(data_list = sim$data_list, burnin = 200, nsave = 100)
cm <- plot_recovery(fit, sim$adj_list)

cm$Group_1  # confusion metrics for group 1
#>         TP         FP         TN         FN        TPR        FPR 
#>  8.0000000  0.0000000 15.0000000  5.0000000  0.6153846  0.0000000