compareDAGs: Comparing two graphs

In BiDAG: Bayesian Inference for Directed Acyclic Graphs

Comparing two graphs

Description

This function compares one (estimated) graph to another graph (true graph), returning a vector of 8 values:

• the number of true positive edges ('TP') is the number of edges in the skeleton of 'egraph' which are also present in the skeleton of 'truegraph'

• the number of false positive edges ('FP') is the number of edges in the skeleton of 'egraph' which are absent in the skeleton of 'truegraph'

• the number of fralse negative edges ('FN') is the number of edges in the skeleton of 'truegraph' which are absent in the skeleton of 'egraph'

• structural Hamming distance ('SHD') between 2 graphs is computed as TP+FP+the number of edges with an error in direction

• TPR equals TP/(TP+FN)

• FPR equals FP/(TN+FP) (TN stands for true negative edges)

• FPRn equals FP/(TP+FN)

• FDR equals FP/(TP+FP)

Usage

compareDAGs(egraph, truegraph, cpdag = FALSE, rnd = 2)

Arguments

egraph	an object of class graphNEL (package ‘graph’), representing the graph which should be compared to a ground truth graph or an ajecency matrix corresponding to the graph
truegraph	an object of class graphNEL (package ‘graph’), representing the ground truth graph or an ajecency matrix corresponding to this graph
cpdag	logical, if TRUE (FALSE by default) both graphs are first converted to their respective equivalence class (CPDAG); this affects SHD calculation
rnd	integer, rounding integer indicating the number of decimal places (round) when computing TPR, FPR, FPRn and FDR

Value

a named numeric vector 8 elements: SHD, number of true positive edges (TP), number of false positive edges (FP), number of false negative edges (FN), true positive rate (TPR), false positive rate (FPR), false positive rate normalized to the true number of edges (FPRn) and false discovery rate (FDR)

Examples

Asiascore<-scoreparameters("bde", Asia)
## Not run: 
eDAG<-learnBN(Asiascore,algorithm="order")
compareDAGs(eDAG$DAG,Asiamat)

## End(Not run)

BiDAG documentation built on May 31, 2023, 6:46 p.m.