-#' Plot
+#' Plot
#'
#' It is a function which plots relevant parameters
#'
for (r in 1:K)
{
Melt <- melt(t((model$phi[, , r])))
- gReg[[r]] <- ggplot(data = Melt, aes(x = Var1, y = Var2, fill = value)) +
- geom_tile() + scale_fill_gradient2(low = "blue", high = "red", mid = "white",
+ gReg[[r]] <- ggplot(data = Melt, aes(x = Var1, y = Var2, fill = value)) +
+ geom_tile() + scale_fill_gradient2(low = "blue", high = "red", mid = "white",
midpoint = 0, space = "Lab") + ggtitle(paste("Regression matrices in cluster", r))
}
print(gReg)
Melt <- melt(t(model$phi[, , k1] - model$phi[, , k2]))
gDiff <- ggplot(data = Melt, aes(x = Var1, y = Var2, fill = value))
+ geom_tile()
- + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
+ + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
space = "Lab")
- + ggtitle(paste("Difference between regression matrices in cluster",
+ + ggtitle(paste("Difference between regression matrices in cluster",
k1, "and", k2))
print(gDiff)
}
matCov[, r] <- diag(model$rho[, , r])
MeltCov <- melt(matCov)
gCov <- ggplot(data = MeltCov, aes(x = Var1, y = Var2, fill = value)) + geom_tile()
- + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
+ + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
space = "Lab")
+ ggtitle("Covariance matrices")
print(gCov)