bma_posterior function

Compute Posterior Distributions from Graph Search Results

The bma_posterior function samples posterior distributions of graph parameters (e.g., partial correlations or precision matrices) based on the graph structures sampled during a Bayesian graph search performed by ggm_search.

bma_posterior(object, param = "pcor", iter = 5000, progress = TRUE)

Arguments

• object: A ggm_search object
• param: Compute BMA on either partial correlations "pcor" (default) or on precision matrix "Theta".
• iter: Number of samples to be drawn, defaults to 5,000
• progress: Show progress bar, defaults to TRUE

Returns

A list containing posterior samples and the Bayesian Model Averaged parameter estimates.

Details

This function incorporates uncertainty in both graph structure and parameter estimation, providing Bayesian Model Averaged (BMA) parameter estimates.

Use bma_posterior when detailed posterior inference on graph parameters is needed, or to refine results obtained from ggm_search.

See Also

ggm_search