  In this work, we develop multivariate functional singular spectrum analysis
(MFSSA) over different dimensional domains which is the functional extension of
multivariate singular spectrum analysis (MSSA). In the following, we provide
all of the necessary theoretical details supporting the work as well as the
implementation strategy that contains the recipes needed for the algorithm. We
provide a simulation study showcasing the better performance in reconstruction
accuracy of a multivariate functional time series (MFTS) signal found using
MFSSA as compared to other approaches and we give a real data study showing how
MFSSA enriches analysis using intraday temperature curves and remote sensing
images of vegetation. MFSSA is available for use through the Rfssa R package.
