The R package â€˜netSEMâ€™ conducts a net-SEM statistical analysis (network structural equation modeling) on a data frame of coincident observations of multiple continuous variables. Principle 1 generates an inferential model through pairwise correlation of variables based on the Markovian Spirit. Principle 2 provides a predictive model through multiple regression with the model complexity and performance evaluated using either Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC) specified by the user.

This is a simple example for generating degradation models using netSEM principle 1 and principle 2.

```
# Load in netSEM library
library(netSEM)
# Load in example data
data(acrylic)
# Perform principle 1 and principle 2
<- netSEMp1(acrylic)
acrylic_p1 <- netSEMp2(acrylic, criterion = "AIC") #AIC by default
acrylic_p2 # Plotting netSEM diagrams
plot(acrylic_p1, cutoff = c(0.3,0.6,0.8))
plot(acrylic_p2, cutoff = c(0.3,0.6,0.8))
```