Linear mixed modeling (LMM) is a comprehensive technique used for clustered, panel and
longitudinal data. The main assumption of classical LMM is having normally distributed
random effects and error terms. However, there are several situations for that we need to use
heavier tails distributions than the (multivariate) normal to handle outliers and/or heavy
tailness in data. In this study, we focus on LMM using the multivariate Laplace distribution
which is known as the heavy tailed alternative to the normal distribution. The parameter …

Linear mixed modeling (LMM) is a comprehensive technique used for clustered, panel and
longitudinal data. The main assumption of classical LMM is having normally distributed
random effects and error terms. However, there are several situations for that we need to use
heavier tails distributions than the (multivariate) normal to handle outliers and/or heavy
tailness in data. In this study, we focus on LMM using the multivariate Laplace distribution
which is known as the heavy tailed alternative to the normal distribution. The parameter …