Quantile regression for longitudinal data via the multivariate generalized hyperbolic distribution

While extensive research has been devoted to univariate quantile regression, this is considerably less the case for multivariate (longitudinal) version, even though there are many potential applications, such as joint examination of growth curves two or more characteristics, body weight and length in infants. Quantile functions easier interpret a population than mean functions. connection between quantiles asymmetric Laplace distribution known, it well known that its use maximum likelihood estimation poses mathematical computational challenges. Therefore, we study broader family generalized hyperbolic distributions, which limiting case. We offer an asymptotic treatment. Simulations data example supplement modelling theoretical considerations.