frobenius {EGAnet} | R Documentation |
Frobenius Norm (Similarity)
Description
Computes the Frobenius Norm (Ulitzsch et al., 2023)
Usage
frobenius(network1, network2)
Arguments
network1 |
Matrix or data frame. Network to be compared |
network2 |
Matrix or data frame. Second network to be compared |
Value
Returns Frobenius Norm
Author(s)
Hudson Golino <hfg9s at virginia.edu> & Alexander P. Christensen <alexander.christensen at Vanderbilt.Edu>
References
Simulation Study
Ulitzsch, E., Khanna, S., Rhemtulla, M., & Domingue, B. W. (2023).
A graph theory based similarity metric enables comparison of subpopulation psychometric networks
Psychological Methods.
Examples
# Obtain wmt2 data
wmt <- wmt2[,7:24]
# Set seed (for reproducibility)
set.seed(1234)
# Split data
split1 <- sample(
1:nrow(wmt), floor(nrow(wmt) / 2)
)
split2 <- setdiff(1:nrow(wmt), split1)
# Obtain split data
data1 <- wmt[split1,]
data2 <- wmt[split2,]
# Perform EBICglasso
glas1 <- EBICglasso.qgraph(data1)
glas2 <- EBICglasso.qgraph(data2)
# Frobenius norm
frobenius(glas1, glas2)
# 0.7070395
[Package EGAnet version 2.3.0 Index]