17. The method of claim 15 , wherein the time partitioned data comprise binned data, the method further comprising: classifying the time partitioned data according to the plurality of classes, to form binned and classified data.
15. The method of claim 14 , wherein the input parameters comprise a time step parameter, and wherein developing an architecture for a Markov model from the data series and the time step parameter comprises: partitioning the data series according to the time step parameter to form time partitioned data; developing a plurality of classes from the time partitioned data and the input parameters; and associating a state of the Markov model with a class of the plurality of classes.