Krone T, Albers CJ, Kuppens P, Timmerman ME.
In emotion dynamic research, one distinguishes various elementary emotion dynamic features, which are studied using intensive longitudinal data. Typically, each emotion dynamic feature is quantified separately, which hampers the study of relationships between various features. Further, the length of the observed time series in emotion research is limited and often suffers from a high percentage of missing values. In this article, we propose a vector autoregressive Bayesian dynamic model that is useful for emotion dynamic research.