arima analysis after clustering time series I have a database of multivariate time series that I want to cluster in order to find natural grouping of features. I am thinking of taking each cluster points and perform an ARIMA analysis on its points. Within those clusters, what should be the best way to infer those groupings in the original mutltidimentional feature space? 
a sample of my time series is :

TimeStamp       | Sensor0 | Sensor1| Sensor2
2015-02-05 11:30|&lt;Min     | On     | off
2015-02-05 11:31|&lt;Min     | on     | off 
2015-02-05 11:32| Action2 | 10     | 0.0001  
2015-02-07 11:33| Action2 | 10     | 0.00012 
2015-02-07 11:34| Action2 | 10     | 0.00012 
2015-02-07 11:35| Action2 | 20     | 0.00015 


I have roughly 10 separate groupings and I don't think performing different ARIMA calculations would be the best efficient method. Any thoughts or ideas are also welcome!
Here's a reference for your problem. If you read the first two pages, you'll get a hint at what features to use for time series clustering.

https://www.jstatsoft.org/article/view/v062i01