Start your journey into machine learning with EEG time-series data in this easy-to-follow Python project. Perfect for ...

Time series forecasting applications The applications of time series models are many and wide-ranging, from sales forecasting to weather forecasting.

This paper develops an asymptotic theory for estimated change-points in linear and nonlinear time series models. Based on a measurable objective function, it is shown that the estimated change-point ...

The implications of this shift are profound. Traditional time series models, while reliable in stable conditions, can fall short when faced with sudden economic shifts or unprecedented events.

From time to time, papers in bordering fields are published. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, ...