This paper concerns statistical estimation of the partially linear model (PLM) for time course measurements, which are temporally correlated and allow multiple-run for repeated measurements to enhance
The collection of ECL, WTH, ETT, Solar, Traffic dataset used as benchmark in our work "Long-term 5G network traffic forecasting via modeling non-stationarity with deep learning"
Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests t
