I have been playing with time series data and using models like facebook prophet which uses time series decomposition and models the signal using trend, seasonalities and holidays.
The stuff I found about these time series methods use time as the independent variable and a scalar value as the dependent variable. What about time series models with multiple y-values.
As an example, in my case I am tracking people and I track the counts of people but also the average speed at which they move through a particular section of a shop. Also, there may also be a correlation between these quantities. Are there established time series modelling techniques which can use such multi variate and non independent data sources?