The R package ‘netSEM’ 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.

netSEM Usage

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

# Load in netSEM library
# Load in example data
# Perform principle 1 and principle 2
acrylic_p1 <- netSEMp1(acrylic)
acrylic_p2 <- netSEMp2(acrylic, criterion = "AIC") #AIC by default
# 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))