performance (version 0.12.4)

check_multimodal: Check if a distribution is unimodal or multimodal

Description

For univariate distributions (one-dimensional vectors), this functions performs a Ameijeiras-Alonso et al. (2018) excess mass test. For multivariate distributions (data frames), 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.

Usage

check_multimodal(x, ...)

Arguments

x

A numeric vector or a data frame.

...

Arguments passed to or from other methods.

References

• Ameijeiras-Alonso, J., Crujeiras, R. M., and Rodríguez-Casal, A. (2019). Mode testing, critical bandwidth and excess mass. Test, 28(3), 900-919.

Examples

if (FALSE) { # require("multimode") && require("mclust")
# \donttest{
# Univariate
x <- rnorm(1000)
check_multimodal(x)

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)
# }
}