I am currently working on some time series data, I know I can use LOESS/ARIMA model.
The data is written to a vector whose length is 1000, which is a queue, updating every 15 minutes,
Thus the old data will pop out while the new data push in the vector.
I can rerun the whole model on a scheduler, e.g. retrain the model every 15 minutes, that is, Use the whole 1000 value to train the LOESS model, However it is very inefficient, as every time only one value is insert while another 999 vlaues still same as last time.
So how can I achieve better performance?