NonSTOP: A NonSTationary Online Prediction Method for Time Series.

We present online prediction methods for time series that let us explicitly handle nonstationary artifacts (e.g., trend and seasonality) present in most real time series. Specifically, we show that applying appropriate transformations to such time series before prediction can lead to improved theoretical and empirical prediction performance. Moreover, since these transformations are usually unknow...