The behaviour of many processes in science and engineering can be accurately described by dynamical system models consisting of a set of ordinary differential equations (ODEs). Often these models have
Developed MATLAB code and simulation data for the Mozart effect study. The code requires the Bayesian topology identification code and the MVGC toolbox to run (see references).
We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional an
