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 0.229 0.063
#> B1--B3 0.063 0.064
#> B2--B3 0.492 0.055
#> B1--B4 0.333 0.062
#> B2--B4 -0.030 0.068
#> B3--B4 0.212 0.066
#> B1--B5 0.157 0.063
#> B2--B5 0.099 0.067
#> B3--B5 0.183 0.063
#> B4--B5 0.345 0.060
#> ---
# }
