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)
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