library(exactICLforLCA)
library(BayesLCA)
library(ggplot2)
# Read data
data(Alzheimer)
## set CONSTANTS
alpha_var <- 1
beta_var <- 1
delta_var <- 1
# G <- as.integer(readline(prompt="Enter the number of groups: "))
G <- 7
# LCA fit
fit <- blca.em(Alzheimer, G)
Z <- unMAP(MAP(Zscore(Alzheimer, fit)))
Y <- as.matrix(Alzheimer)
res <- ICLFit(Z, Y, G, alpha_var, beta_var, delta_var)
ICLsummary()
# extra - BEGIN
z_new <- res$Z_max
z_new_sum <- apply(z_new, 2, sum)
apply(z_new, 2, sum)/nrow(z_new)
theta_hat_new <- t(z_new) %*% as.matrix(Alzheimer)
theta_hat_new <- theta_hat_new / z_new_sum
theta_hat_new
r <- barplot(theta_hat_new, main="'exactICLforLCA' model fit",
xlab="SYMPTOMS",col=c('#004c6d','#7fa9c9'),
legend = rownames(theta_hat_new), beside=TRUE)
legend("topleft",
legend = c("Group 1"),
col = c('#004c6d'),
pch = c(15,25),
bty = "n",
pt.cex = 2,
cex = 1.2,
text.col = "black",
horiz = F ,
inset = c(0.05, 0.05))
legend("topleft",
legend = c("Group 2"),
col = c('#7fa9c9'),
pch = c(15,25),
bty = "n",
pt.cex = 2,
cex = 1.2,
text.col = "black",
horiz = F ,
inset = c(0.05, 0.1))
# extra - EnD
#extra - BEGIN
fit <- blca.em(Alzheimer, 2)
Z <- unMAP(MAP(Zscore(Alzheimer, fit)))
Zsum <- apply(Z, 2, sum)
apply(Z, 2, sum)/nrow(Z)
theta_hat <- t(Z) %*% as.matrix(Alzheimer)
theta_hat <- theta_hat / Zsum
theta_hat
r <- barplot(theta_hat, main="Expectation–Maximization algorithm (blca.em) fit",
xlab="SYMPTOMS",col=c('#004c6d','#7fa9c9'),
legend = rownames(theta_hat), beside=TRUE)
usr <- par("usr")
par(usr=c(usr[0:2], 0, 1))
axis(2,at=seq(0,1,1))
legend("topleft",
legend = c("Group 1"),
col = c('#004c6d'),
pch = c(15,25),
bty = "n",
pt.cex = 2,
cex = 1.2,
text.col = "black",
horiz = F ,
inset = c(0.05, 0.05))
legend("topleft",
legend = c("Group 2"),
col = c('#7fa9c9'),
pch = c(15,25),
bty = "n",
pt.cex = 2,
cex = 1.2,
text.col = "black",
horiz = F ,
inset = c(0.05, 0.1))
## extra - END
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