Check if a distribution is unimodal or multimodal
For univariate distributions (one-dimensional vectors), this functions performs a Ameijeiras-Alonso et al. (2018) excess mass test. For multivariate distributions (dataframes), it uses mixture modelling. However, it seems that it always returns a significant result (suggesting that the distribution is multimodal). A better method might be needed here.
check_multimodal(x, ...)
x |
A numeric vector or a data frame. |
... |
Arguments passed to or from other methods. |
Ameijeiras-Alonso, J., Crujeiras, R. M., \& Rodríguez-Casal, A. (2019). Mode testing, critical bandwidth and excess mass. Test, 28(3), 900-919.
## Not run:
if (require("multimode")) {
# Univariate
x <- rnorm(1000)
check_multimodal(x)
}
if (require("multimode") && require("mclust")) {
x <- c(rnorm(1000), rnorm(1000, 2))
check_multimodal(x)
# Multivariate
m <- data.frame(
x = rnorm(200),
y = rbeta(200, 2, 1)
)
plot(m$x, m$y)
check_multimodal(m)
m <- data.frame(
x = c(rnorm(100), rnorm(100, 4)),
y = c(rbeta(100, 2, 1), rbeta(100, 1, 4))
)
plot(m$x, m$y)
check_multimodal(m)
}
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.