ising_model_template

Ising Model

library("IsingFit")
library("qgraph")
library("Matrix")
library("glmnet")
library("IsingSampler")

lapply(c("IsingFit","qgraph","Matrix","glmnet","IsingSampler","psych"), 
library, character.only=T)


data <- repmis::source_DropboxData("marcela_network.csv",
                                  "62e4d6emy0aa25i",
                                  sep = ",",
                                  header = TRUE)

summary(data)
cor_data<-polychoric(data)
dataMatrix <- t(as.matrix(data)) %*% as.matrix(data)

summary(data)
color<-c("red",rep(c("steelblue"),33),rep(c("gold"),11),rep(c("lightgreen"),11))
freq<-c()

qgraph(dataMatrix, layout="spring",vsize = 5,esize=3, cut = 8,
  minimum = 0,color=color) 



data_risk <- repmis::source_DropboxData("marcela_data.csv",
                                  "wi038s1n4ahpgxw",
                                  sep = ",",
                                  header = TRUE)


risk<-data.frame(data,data_risk$CLASS.ESCORE)

par(nrow(3:1))
risk_verde<-subset(risk,risk$data_risk.CLASS.ESCORE=='VERDE')
risk_verde<-remove.vars(risk_verde,c("data_risk.CLASS.ESCORE"))
dataMatrix <- t(as.matrix(risk_verde)) %*% as.matrix(risk_verde)
qgraph(dataMatrix, layout="spring",vsize = 5,esize=3, cut = 5,
  minimum = 5,color=color) 

risk_amarelo<-subset(risk,risk$data_risk.CLASS.ESCORE=='AMARELO')
risk_amarelo<-remove.vars(risk_amarelo,c("data_risk.CLASS.ESCORE"))
dataMatrix <- t(as.matrix(risk_amarelo)) %*% as.matrix(risk_amarelo)
qgraph(dataMatrix, layout="spring",vsize = 5,esize=3, cut = 5,
  minimum = 5,color=color) 

risk_amarelo<-subset(risk,risk$data_risk.CLASS.ESCORE=='VERMELHO')
risk_amarelo<-remove.vars(risk_amarelo,c("data_risk.CLASS.ESCORE"))
dataMatrix <- t(as.matrix(risk_amarelo)) %*% as.matrix(risk_amarelo)
qgraph(dataMatrix, layout="spring",vsize = 5,esize=3, cut = 5,
  minimum = 5,color=color) 


library(pcalg)
names<-rownames(dataMatrix)
n = nrow(dataMatrix)
p = ncol(dataMatrix)
## define independence test (partial correlations)
indepTest <- disCItest
## define sufficient statistics
suffStat <- list(dm = dataMatrix, adaptDF=FALSE)
## estimate CPDAG
alpha <- 0.01
pc.fit <- pc(suffStat, indepTest, alpha,names,verbose=TRUE)

qgraph(pc.fit)
plot(pc.fit, main = "",labels=names)



IsingFit(data,plot=TRUE)