  In this article, we propose joint location, scale and skewness models of the
skew Laplace normal (SLN) distribution as an alternative model for joint
modelling location, scale and skewness models of the skew-t-normal (STN)
distribution when the data set contains both asymmetric and heavy-tailed
observations. We obtain the maximum likelihood (ML) estimators for the
parameters of the joint location, scale and skewness models of the SLN
distribution using the expectation-maximization (EM) algorithm. The performance
of the proposed model is demonstrated by a simulation study and a real data
example.
