I do not know much about R, but if there are methods to analyse univariate time series, probably the first step will be to make the multivariate data univariate.
I assume you have a tuple containing different types (e.g. a mixture of bool, emueration or real valued data) for each time step.
You could e.g. take an Restricted Boltzman Machine like algorithm and extract the features of thoses tuples into a univariate real (or boolean) valued vector. Then you feed this univariate time series into the R routienes.
This paper describes a way to feed multivariate int a RBM. I found it quite nice! :)
Be aware, that rebuilding their work (in R?) will likely cost a significant amount of time!