library(mvtnorm)
# Data simulation (Bivariate-t on positive quadrant)
rho <- 0.5
sigma <- matrix(c(1, rho, rho, 1), ncol = 2)
df <- 2
set.seed(101)
n <- 1500
data <- rmvt(5 * n, sigma = sigma, df = df)
data <- data[data[, 1] > 0 & data[, 2] > 0, ]
data <- data[1:n, ]
P <- c(1 / 750, 1 / 1500, 1 / 3000)
ell1 <- ellipse(prob = 1 - P[1], sigma = sigma, df = df, pos = TRUE)
ell2 <- ellipse(prob = 1 - P[2], sigma = sigma, df = df, pos = TRUE)
ell3 <- ellipse(prob = 1 - P[3], sigma = sigma, df = df, pos = TRUE)
plot(
data,
xlim = c(0, max(data[, 1], ell1[, 1], ell2[, 1], ell3[, 1])),
ylim = c(0, max(data[, 2], ell1[, 2], ell2[, 2], ell3[, 2])),
pch = 19
)
points(ell1, type = "l", lwd = 2, lty = 1)
points(ell2, type = "l", lwd = 2, lty = 1)
points(ell3, type = "l", lwd = 2, lty = 1)
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