I have a time series dataset that looks like this
x y z
t
2017-10-28 00:00:01 0.18 0.01 0.55
2017-10-28 00:00:02 0.20 0.01 0.56
2017-10-28 00:00:03 0.24 0.01 0.57
2017-10-28 00:00:04 0.23 0.02 0.58
2017-10-28 00:00:05 0.26 0.01 0.59
... ... ... ...
2017-10-28 12:59:08 0.53 -0.03 0.9
2017-10-28 12:59:09 0.56 -0.04 0.89
2017-10-28 01:00:00 0.57 -0.04 ???
give (x) & (y) at time (t) I want a chose a model that will best predict the next value in the sequence (z)
notes:
• the time series is stationary - i have detrended, deaseasonlized, and minmax scaled each feature