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Summarize a multiggm_fit object

summary.multiggm_fit.Rd

Displays MCMC diagnostics including acceptance rates, edge counts at a given PIP threshold, and graph similarity (theta) estimates.

Usage

# S3 method for class 'multiggm_fit'
summary(object, pip_threshold = 0.5, ...)

Arguments

object

A multiggm_fit object returned by multiggm_mcmc.

pip_threshold

Numeric threshold for counting selected edges via posterior inclusion probability (PIP). Default 0.5.

...

Ignored.

Value

An object of class "summary.multiggm_fit" (printed invisibly) with components:

K

Integer; number of groups.

p

Integer; number of variables.

nsave

Integer; number of saved posterior draws.

ar_gamma

Numeric; mean acceptance rate for between-model (spike-slab toggle) moves on theta.

ar_theta

Numeric; mean acceptance rate for within-model (slab-to-slab) moves on theta.

ar_nu

Numeric; mean acceptance rate for nu updates.

edge_counts

Integer vector of length K; number of selected edges per group at the given PIP threshold.

pip_threshold

The PIP threshold used.

theta_mean

Numeric matrix [K, K]; posterior mean of theta (graph similarity) for each pair of groups. Upper triangle only.

theta_nonzero_frac

Numeric matrix [K, K]; posterior probability that theta > 0 for each pair. Upper triangle only.

hyper

Named list of hyperparameters used in the fit.

See also

multiggm_mcmc(), pip_edges()

Examples

sim <- simulate_multiggm(K = 2, p = 8, n = 80, seed = 1)
fit <- multiggm_mcmc(data_list = sim$data_list, burnin = 200, nsave = 100)
summary(fit)
#> multiGGM MCMC Summary
#> =====================
#> Groups (K): 2   |  Nodes (p): 8   |  Posterior draws: 100 
#> 
#> Acceptance rates:
#>   gamma (edge toggle): 7.7% 
#>   theta (within-model): 62.7% 
#>   nu (edge log-odds): 56.0% 
#> 
#> Selected edges (PIP >= 0.5 ):
#>   Group 1 : 8 edges
#>   Group 2 : 7 edges
#> 
#> Graph similarity (theta):
#>   theta[1,2]: mean = 0.493, P(nonzero) = 97.0%
#> 
summary(fit, pip_threshold = 0.3)
#> multiGGM MCMC Summary
#> =====================
#> Groups (K): 2   |  Nodes (p): 8   |  Posterior draws: 100 
#> 
#> Acceptance rates:
#>   gamma (edge toggle): 7.7% 
#>   theta (within-model): 62.7% 
#>   nu (edge log-odds): 56.0% 
#> 
#> Selected edges (PIP >= 0.3 ):
#>   Group 1 : 11 edges
#>   Group 2 : 10 edges
#> 
#> Graph similarity (theta):
#>   theta[1,2]: mean = 0.493, P(nonzero) = 97.0%
#>