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Ultán P. Doherty 2025-05-08
gross_gmm_k3n1000o10 <- find_gross(gmm_k3n1000o10[, 1:2], max_out = 20)
ombc_gmm_k3n1000o10 <- ombc_gmm(
gmm_k3n1000o10[, 1:2], comp_num = 3, max_out = 20, gross_outs = gross_gmm_k3n1000o10$gross_bool
)
print(ombc_gmm_k3n1000o10)## Starting number of data points: 1010
## Maximum number of outliers: 20
## Number of gross outliers: 5
## Final number of outliers: 10 (minimum dissimilarity)plot(ombc_gmm_k3n1000o10)
gmm_k3n1000o10 |>
mutate("ombc" = as.factor(ombc_gmm_k3n1000o10$labels), G = as.factor(G)) |>
ggplot(aes(x = X1, y = X2, colour = ombc, shape = G)) +
geom_point() +
labs(colour = "outlierMBC", shape = "Simulation") +
ggokabeito::scale_colour_okabe_ito(order = c(9, 1:3))
gross_lcwm_k3n1000o10 <- find_gross(lcwm_k3n1000o10[, 1:2], max_out = 20)
ombc_lcwm_k3n1000o10 <- ombc_gmm(
lcwm_k3n1000o10[, 1:2], comp_num = 3, max_out = 20, gross_outs = gross_lcwm_k3n1000o10$gross_bool
)
print(ombc_lcwm_k3n1000o10)## Starting number of data points: 1010
## Maximum number of outliers: 20
## Number of gross outliers: 0
## Final number of outliers: 10 (minimum dissimilarity)plot(ombc_lcwm_k3n1000o10)
lcwm_k3n1000o10 |>
mutate("ombc" = as.factor(ombc_lcwm_k3n1000o10$labels), G = as.factor(G)) |>
ggplot(aes(x = X1, y = Y, colour = ombc, shape = G)) +
geom_point() +
labs(colour = "outlierMBC", shape = "Simulation") +
ggokabeito::scale_colour_okabe_ito(order = c(9, 1:3))
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