We present a Bayesian approach for modeling multivariate, dependent functional data. To
account for the three dominant structural features in the data—functional, time dependent,
and multivariate components—we extend hierarchical dynamic linear models for
multivariate time series to the functional data setting. We also develop Bayesian spline
theory in a more general constrained optimization framework. The proposed methods
identify a time-invariant functional basis for the functional observations, which is smooth and …

… Assume that we observe multiple time series of functional data: … We started research on
functional dynamic models to understand • interrelationships between yields in different
economies and • effects of government policies on yields. • Of particular interest is Quantitative
Easing (QE). • Under QE, the government bought massive amounts of long-maturity bonds to lower
long-term interest rates. • … With the multivariate functional dynamic linear model it is easy to: …