# Example, Eiko Fried, February 6th 2016

library(qgraph)
library(bootnet)
library(psych)

# continuous case (Gaussian Graphical Model)
set.seed(1337)
data1 <- data.frame(matrix(rnorm(500), 50, 10))
data1$X10 <- rnorm(50)+0.9*data1$X9 
network1 <- estimateNetwork(data1, default="EBICglasso")
plot(network1)

write.csv(cor_auto(data1), file="correlation_matrix.csv")
write.csv(getWmat(network1), file="AdjacencyMatrix_GaussianGraphicalModel.csv")


# binary case (Ising Model)
set.seed(1337)
data2 <- data.frame(matrix(rbinom(9*500, 1, .5), ncol=9))
data2$X10 <- data2$X9
data2$X10[400:499] <- rbinom(100, 1, .5)
network2 <- estimateNetwork(data2, default="IsingFit")
plot(network2)

write.csv(tetrachoric(data2)$rho, file="tetrachoric_rho.csv")
write.csv(tetrachoric(data2)$tau, file="tetrachoric_tau.csv")
write.csv(network2$results$weiadj, file="AdjacencyMatrix_IsingModel.csv")
write.csv(network2$results$thresholds, file="Thresholds_IsingModel.csv")