Abstract:
Bimodal distributions have rarely been studied although they appear frequently in datasets.
We develop a novel bimodal distribution based on the triangular distribution and then expand it to
the multivariate case using a Gaussian copula. To determine the goodness of fit of the univariate
model, we use the Kolmogorov–Smirnov (KS) and Cramér–von Mises (CVM) tests. The contributions
of this work are that a simplistic yet robust distribution was developed to deal with bimodality in
data, a multivariate distribution was developed as a generalisation of this univariate distribution
using a Gaussian copula, a comparison between parametric and semi-parametric approaches to
modelling bimodality is given, and an R package called btld is developed from the workings of
this paper.
