Copulae for non-continuous distributions

Copulas are a popular choice when assessing the dependence structure between continuous random variables. However, major difficulties arise as soon as one of the random variables is non-continuous. This thesis introduces the basics of copula theory based on the cited literature. The main focus of this thesis is to introduce the reader to the field of non- continuous copula modelling and highlight all major issues. At the same time, empirical evidence with discussion is presented to suggest that copula modelling and inference may be a viable option when additional care and caution are applied. Afterwards, accumulated theoretical knowledge is demonstrated on real-world data concerning bike-sharing