Summarize the posterior distribution for each partial correlation with the posterior mean and standard deviation.
Usage
# S3 method for class 'explore'
summary(object, col_names = TRUE, ...)
Examples
# \donttest{
# note: iter = 250 for demonstrative purposes
Y <- ptsd[,1:5]
fit <- explore(Y, iter = 250,
progress = FALSE)
summ <- summary(fit)
summ
#> BGGM: Bayesian Gaussian Graphical Models
#> ---
#> Type: continuous
#> Analytic: FALSE
#> Formula:
#> Posterior Samples: 250
#> Observations (n):
#> Nodes (p): 5
#> Relations: 10
#> ---
#> Call:
#> explore(Y = Y, iter = 250, progress = FALSE)
#> ---
#> Estimates:
#> Relation Post.mean Post.sd
#> B1--B2 0.228 0.065
#> B1--B3 0.056 0.072
#> B2--B3 0.498 0.052
#> B1--B4 0.325 0.059
#> B2--B4 -0.025 0.074
#> B3--B4 0.223 0.062
#> B1--B5 0.156 0.066
#> B2--B5 0.098 0.064
#> B3--B5 0.189 0.068
#> B4--B5 0.337 0.064
#> ---
# }